File IndexRefine.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 IndexRefine : public faiss::Index
#include <IndexRefine.h>

Index that queries in a base_index (a fast one) and refines the results with an exact search, hopefully improving the results.

Subclassed by faiss::IndexRefineFlat

Public Functions

IndexRefine(Index *base_index, Index *refine_index)

initialize from empty index

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

Perform training on a representative set of vectors

Parameters
  • n – nb of training vectors

  • x – training vecors, size n * d

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 reset() override

removes all elements from the database.

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

query n vectors of dimension d to the index.

return at most k vectors. If there are not enough results for a query, the result array is padded with -1s.

Parameters
  • x – input vectors to search, size n * d

  • labels – output labels of the NNs, size n*k

  • distances – output pairwise distances, size n*k

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)

~IndexRefine() override

Public Members

Index *base_index

faster index to pre-select the vectors that should be filtered

Index *refine_index

refinement index

bool own_fields

should the base index be deallocated?

bool own_refine_index

same with the refinement index

float k_factor = 1

factor between k requested in search and the k requested from the base_index (should be >= 1)

struct IndexRefineFlat : public faiss::IndexRefine
#include <IndexRefine.h>

Version where the refinement index is an IndexFlat. It has one additional constructor that takes a table of elements to add to the flat refinement index

Public Functions

explicit IndexRefineFlat(Index *base_index)
IndexRefineFlat(Index *base_index, const float *xb)
IndexRefineFlat()
virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override

query n vectors of dimension d to the index.

return at most k vectors. If there are not enough results for a query, the result array is padded with -1s.

Parameters
  • x – input vectors to search, size n * d

  • labels – output labels of the NNs, size n*k

  • distances – output pairwise distances, size n*k

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

Perform training on a representative set of vectors

Parameters
  • n – nb of training vectors

  • x – training vecors, size n * d

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 reset() override

removes all elements from the database.

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)

Public Members

Index *base_index

faster index to pre-select the vectors that should be filtered

Index *refine_index

refinement index

bool own_fields

should the base index be deallocated?

bool own_refine_index

same with the refinement index

float k_factor = 1

factor between k requested in search and the k requested from the base_index (should be >= 1)