File DistanceComputer.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.

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. 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)

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. 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.

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. 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.

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 DistanceComputer

Subclassed by faiss::FlatCodesDistanceComputer, faiss::NegativeDistanceComputer

Public Functions

virtual void set_query(const float *x) = 0

called before computing distances. Pointer x should remain valid while operator () is called

virtual float operator()(idx_t i) = 0

compute distance of vector i to current query

inline virtual void distances_batch_4(const idx_t idx0, const idx_t idx1, const idx_t idx2, const idx_t idx3, float &dis0, float &dis1, float &dis2, float &dis3)

compute distances of current query to 4 stored vectors. certain DistanceComputer implementations may benefit heavily from this.

virtual float symmetric_dis(idx_t i, idx_t j) = 0

compute distance between two stored vectors

inline virtual ~DistanceComputer()
struct NegativeDistanceComputer : public faiss::DistanceComputer

Public Functions

inline explicit NegativeDistanceComputer(DistanceComputer *basedis)
inline virtual void set_query(const float *x) override

called before computing distances. Pointer x should remain valid while operator () is called

inline virtual float operator()(idx_t i) override

compute distance of vector i to current query

inline virtual void distances_batch_4(const idx_t idx0, const idx_t idx1, const idx_t idx2, const idx_t idx3, float &dis0, float &dis1, float &dis2, float &dis3) override

compute distances of current query to 4 stored vectors. certain DistanceComputer implementations may benefit heavily from this.

inline virtual float symmetric_dis(idx_t i, idx_t j) override

compute distance between two stored vectors

inline virtual ~NegativeDistanceComputer()

Public Members

DistanceComputer *basedis

owned by this

struct FlatCodesDistanceComputer : public faiss::DistanceComputer

Subclassed by faiss::ScalarQuantizer::SQDistanceComputer

Public Functions

inline FlatCodesDistanceComputer(const uint8_t *codes, size_t code_size)
inline FlatCodesDistanceComputer()
inline virtual float operator()(idx_t i) override

compute distance of vector i to current query

virtual float distance_to_code(const uint8_t *code) = 0

compute distance of current query to an encoded vector

inline virtual ~FlatCodesDistanceComputer()
virtual void set_query(const float *x) = 0

called before computing distances. Pointer x should remain valid while operator () is called

inline virtual void distances_batch_4(const idx_t idx0, const idx_t idx1, const idx_t idx2, const idx_t idx3, float &dis0, float &dis1, float &dis2, float &dis3)

compute distances of current query to 4 stored vectors. certain DistanceComputer implementations may benefit heavily from this.

virtual float symmetric_dis(idx_t i, idx_t j) = 0

compute distance between two stored vectors

Public Members

const uint8_t *codes
size_t code_size