File IndexNSG.h

namespace faiss

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree.

Throughout the library, vectors are provided as float * pointers. Most algorithms can be optimized when several vectors are processed (added/searched) together in a batch. In this case, they are passed in as a matrix. When n vectors of size d are provided as float * x, component j of vector i is

x[ i * d + j ]

where 0 <= i < n and 0 <= j < d. In other words, matrices are always compact. When specifying the size of the matrix, we call it an n*d matrix, which implies a row-major storage.

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. I/O functions can read/write to a filename, a file handle or to an object that abstracts the medium.

The read functions return objects that should be deallocated with delete. All references within these objectes are owned by the object.

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Definition of inverted lists + a few common classes that implement the interface.

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Since IVF (inverted file) indexes are of so much use for large-scale use cases, we group a few functions related to them in this small library. Most functions work both on IndexIVFs and IndexIVFs embedded within an IndexPreTransform.

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. In this file are the implementations of extra metrics beyond L2 and inner product

Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Defines a few objects that apply transformations to a set of vectors Often these are pre-processing steps.

struct IndexNSG : public faiss::Index
#include <IndexNSG.h>

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

Subclassed by faiss::IndexNSGFlat

Public Functions

explicit IndexNSG(int d = 0, int R = 32, MetricType metric = METRIC_L2)
explicit IndexNSG(Index *storage, int R = 32)
~IndexNSG() override
void build(idx_t n, const float *x, idx_t *knn_graph, int GK)
virtual void add(idx_t n, const float *x) override

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 chunks smaller than blocksize_add and calls add_core.

Parameters

x – input matrix, size n * d

virtual void train(idx_t n, const float *x) override

Trains the storage if needed.

virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override

entry point for search

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

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)

virtual void reset() override

removes all elements from the database.

void check_knn_graph(const idx_t *knn_graph, idx_t n, int K) const

Public Members

NSG nsg

the link strcuture

bool own_fields

the sequential storage

Index *storage
bool is_built

the index is built or not

int GK

K of KNN graph for building.

char build_type

indicate how to build a knn graph

  • 0: build NSG with brute force search

  • 1: build NSG with NNDescent

int nndescent_S

parameters for nndescent

int nndescent_R
int nndescent_L
int nndescent_iter
struct IndexNSGFlat : public faiss::IndexNSG
#include <IndexNSG.h>

Flat index topped with with a NSG structure to access elements more efficiently.

Public Functions

IndexNSGFlat()
IndexNSGFlat(int d, int R, MetricType metric = METRIC_L2)
void build(idx_t n, const float *x, idx_t *knn_graph, int GK)
virtual void add(idx_t n, const float *x) override

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 chunks smaller than blocksize_add and calls add_core.

Parameters

x – input matrix, size n * d

virtual void train(idx_t n, const float *x) override

Trains the storage if needed.

virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override

entry point for search

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

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)

virtual void reset() override

removes all elements from the database.

void check_knn_graph(const idx_t *knn_graph, idx_t n, int K) const

Public Members

NSG nsg

the link strcuture

bool own_fields

the sequential storage

Index *storage
bool is_built

the index is built or not

int GK

K of KNN graph for building.

char build_type

indicate how to build a knn graph

  • 0: build NSG with brute force search

  • 1: build NSG with NNDescent

int nndescent_S

parameters for nndescent

int nndescent_R
int nndescent_L
int nndescent_iter