File IndexFlatCodes.h

namespace faiss

Implementation of k-means clustering with many variants.

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.

IDSelector is intended to define a subset of vectors to handle (for removal or as subset to search)

PQ4 SIMD packing and accumulation functions

The basic kernel accumulates nq query vectors with bbs = nb * 2 * 16 vectors and produces an output matrix for that. It is interesting for nq * nb <= 4, otherwise register spilling becomes too large.

The implementation of these functions is spread over 3 cpp files to reduce parallel compile times. Templates are instantiated explicitly.

This file contains callbacks for kernels that compute distances.

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.

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.

Definition of inverted lists + a few common classes that implement the interface.

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.

In this file are the implementations of extra metrics beyond L2 and inner product

Implements a few neural net layers, mainly to support QINCo

Defines a few objects that apply transformations to a set of vectors Often these are pre-processing steps.

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

Index that encodes all vectors as fixed-size codes (size code_size). Storage is in the codes vector

Subclassed by faiss::Index2Layer, faiss::IndexAdditiveQuantizer, faiss::IndexFlat, faiss::IndexLSH, faiss::IndexLattice, faiss::IndexNeuralNetCodec, faiss::IndexPQ, faiss::IndexScalarQuantizer

Public Functions

IndexFlatCodes()
IndexFlatCodes(size_t code_size, idx_t d, MetricType metric = METRIC_L2)
virtual void add(idx_t n, const float *x) override

default add uses sa_encode

virtual void reset() override

removes all elements from the database.

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

Reconstruct vectors i0 to i0 + ni - 1

this function may not be defined for some indexes

Parameters:

  • i0 – index of the first vector in the sequence

  • ni – number of vectors in the sequence

  • recons – reconstucted vector (size ni * d)

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 size_t sa_code_size() const override

size of the produced codes in bytes

virtual size_t remove_ids(const IDSelector &sel) override

remove some ids. NB that because of the structure of the index, the semantics of this operation are different from the usual ones: the new ids are shifted

virtual FlatCodesDistanceComputer *get_FlatCodesDistanceComputer() const

a FlatCodesDistanceComputer offers a distance_to_code method

The default implementation explicitly decodes the vector with sa_decode.

inline virtual DistanceComputer *get_distance_computer() const override

Get a DistanceComputer (defined in AuxIndexStructures) object for this kind of index.

DistanceComputer is implemented for indexes that support random access of their vectors.

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

Search implemented by decoding

virtual void range_search(idx_t n, const float *x, float radius, RangeSearchResult *result, const SearchParameters *params = nullptr) const override

query n vectors of dimension d to the index.

return all vectors with distance < radius. Note that many indexes do not implement the range_search (only the k-NN search is mandatory).

Parameters:

  • n – number of vectors

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

  • radius – search radius

  • result – result table

CodePacker *get_CodePacker() const
virtual void check_compatible_for_merge(const Index &otherIndex) const override

check that the two indexes are compatible (ie, they are trained in the same way and have the same parameters). Otherwise throw.

virtual void merge_from(Index &otherIndex, idx_t add_id = 0) override

moves the entries from another dataset to self. On output, other is empty. add_id is added to all moved ids (for sequential ids, this would be this->ntotal)

virtual void add_sa_codes(idx_t n, const uint8_t *x, const idx_t *xids) override

Add vectors that are computed with the standalone codec

Parameters:

  • codes – codes to add size n * sa_code_size()

  • xids – corresponding ids, size n

void permute_entries(const idx_t *perm)

Public Members

size_t code_size
std::vector<uint8_t> codes

encoded dataset, size ntotal * code_size