File simd_result_handlers.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.

Variables

FAISS_API bool simd_result_handlers_accept_virtual

struct SIMDResultHandler

Subclassed by faiss::SIMDResultHandlerToFloat, faiss::simd_result_handlers::DummyResultHandler, faiss::simd_result_handlers::FixedStorageHandler< NQ, BB >, faiss::simd_result_handlers::StoreResultHandler

Public Functions

virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) = 0

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

virtual void set_block_origin(size_t i0, size_t j0) = 0

set the sub-matrix that is being computed

inline virtual ~SIMDResultHandler()

Public Members

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

struct SIMDResultHandlerToFloat : public faiss::SIMDResultHandler

Subclassed by faiss::simd_result_handlers::ResultHandlerCompare< C, false >, faiss::simd_result_handlers::ResultHandlerCompare< C, with_id_map >

Public Functions

inline SIMDResultHandlerToFloat(size_t nq, size_t ntotal)

inline virtual void begin(const float *norms)

inline virtual void end()

virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) = 0

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

virtual void set_block_origin(size_t i0, size_t j0) = 0

set the sub-matrix that is being computed

Public Members

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

namespace simd_result_handlers

Functions

template<class C, bool W, class Consumer, class ...Types>
void dispatch_SIMDResultHanlder_fixedCW(SIMDResultHandler &res, Consumer &consumer, Types... args)

template<class C, class Consumer, class ...Types>
void dispatch_SIMDResultHanlder_fixedC(SIMDResultHandler &res, Consumer &consumer, Types... args)

template<class Consumer, class ...Types>
void dispatch_SIMDResultHanlder(SIMDResultHandler &res, Consumer &consumer, Types... args)

struct DummyResultHandler : public faiss::SIMDResultHandler

#include <simd_result_handlers.h>

Dummy structure that just computes a chqecksum on results (to avoid the computation to be optimized away)

Public Functions

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void set_block_origin(size_t, size_t) final

set the sub-matrix that is being computed

inline ~DummyResultHandler()

Public Members

size_t cs = 0

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

struct StoreResultHandler : public faiss::SIMDResultHandler

#include <simd_result_handlers.h>

memorize results in a nq-by-nb matrix.

j0 is the current upper-left block of the matrix

Public Functions

inline StoreResultHandler(uint16_t *data, size_t ld)

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

Public Members

uint16_t *data

size_t ld

size_t i0 = 0

size_t j0 = 0

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<int NQ, int BB>
struct FixedStorageHandler : public faiss::SIMDResultHandler

#include <simd_result_handlers.h>

stores results in fixed-size matrix.

Public Functions

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

template<class OtherResultHandler>
inline void to_other_handler(OtherResultHandler &other) const

inline virtual ~FixedStorageHandler()

Public Members

simd16uint16 dis[NQ][BB]

int i0 = 0

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<class C, bool with_id_map>
struct ResultHandlerCompare : public faiss::SIMDResultHandlerToFloat

#include <simd_result_handlers.h>

Result handler that compares distances to check if they need to be kept

Subclassed by faiss::simd_result_handlers::RangeHandler< C, false >

Public Types

using TI = typename C::TI

Public Functions

inline ResultHandlerCompare(size_t nq, size_t ntotal, const IDSelector *sel_in)

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

inline virtual ~ResultHandlerCompare()

inline virtual void begin(const float *norms)

inline virtual void end()

virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) = 0

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

Public Members

bool disable = false

int64_t i0 = 0

int64_t j0 = 0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<class C, bool with_id_map = false>
struct SingleResultHandler : public faiss::simd_result_handlers::ResultHandlerCompare<C, false>

#include <simd_result_handlers.h>

Special version for k=1

Public Types

using T = typename C::T

using TI = typename C::TI

using RHC = ResultHandlerCompare<C, with_id_map>

Public Functions

inline SingleResultHandler(size_t nq, size_t ntotal, float *dis, int64_t *ids, const IDSelector *sel_in)

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void end()

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

inline virtual void begin(const float *norms)

Public Members

std::vector<int16_t> idis

float *dis

int64_t *ids

bool disable

int64_t i0

int64_t j0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<class C, bool with_id_map = false>
struct HeapHandler : public faiss::simd_result_handlers::ResultHandlerCompare<C, false>

#include <simd_result_handlers.h>

Structure that collects results in a min- or max-heap

Public Types

using T = typename C::T

using TI = typename C::TI

using RHC = ResultHandlerCompare<C, with_id_map>

Public Functions

inline HeapHandler(size_t nq, size_t ntotal, int64_t k, float *dis, int64_t *ids, const IDSelector *sel_in)

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void end() override

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

inline virtual void begin(const float *norms)

Public Members

std::vector<uint16_t> idis

std::vector<TI> iids

float *dis

int64_t *ids

int64_t k

bool disable

int64_t i0

int64_t j0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<class C, bool with_id_map = false>
struct ReservoirHandler : public faiss::simd_result_handlers::ResultHandlerCompare<C, false>

#include <simd_result_handlers.h>

Simple top-N implementation using a reservoir.

Results are stored when they are below the threshold until the capacity is reached. Then a partition sort is used to update the threshold. Handler built from several ReservoirTopN (one per query)

Public Types

using T = typename C::T

using TI = typename C::TI

using RHC = ResultHandlerCompare<C, with_id_map>

Public Functions

inline ReservoirHandler(size_t nq, size_t ntotal, size_t k, size_t cap, float *dis, int64_t *ids, const IDSelector *sel_in)

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void end() override

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

inline virtual void begin(const float *norms)

Public Members

size_t capacity

float *dis

int64_t *ids

std::vector<TI> all_ids

AlignedTable<T> all_vals

std::vector<ReservoirTopN<C>> reservoirs

bool disable

int64_t i0

int64_t j0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

template<class C, bool with_id_map = false>
struct RangeHandler : public faiss::simd_result_handlers::ResultHandlerCompare<C, false>

#include <simd_result_handlers.h>

Result hanlder for range search. The difficulty is that the range distances have to be scaled using the scaler.

Public Types

using T = typename C::T

using TI = typename C::TI

using RHC = ResultHandlerCompare<C, with_id_map>

Public Functions

inline RangeHandler(RangeSearchResult &rres, float radius, size_t ntotal, const IDSelector *sel_in)

inline virtual void begin(const float *norms) override

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void end() override

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

Public Members

RangeSearchResult &rres

float radius

std::vector<uint16_t> thresholds

std::vector<size_t> n_per_query

size_t q0 = 0

std::vector<Triplet> triplets

bool disable

int64_t i0

int64_t j0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false

struct Triplet

Public Members

idx_t q

idx_t b

uint16_t dis

template<class C, bool with_id_map = false>
struct PartialRangeHandler : public faiss::simd_result_handlers::RangeHandler<C, false>

Public Types

using T = typename C::T

using TI = typename C::TI

using RHC = RangeHandler<C, with_id_map>

Public Functions

inline PartialRangeHandler(RangeSearchPartialResult &pres, float radius, size_t ntotal, size_t q0, size_t q1, const IDSelector *sel_in)

inline void shift_n_per_query()

inline virtual void end() override

inline virtual void begin(const float *norms) override

inline virtual void handle(size_t q, size_t b, simd16uint16 d0, simd16uint16 d1) final

called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.

inline virtual void set_block_origin(size_t i0_in, size_t j0_in) final

set the sub-matrix that is being computed

inline void adjust_with_origin(size_t &q, simd16uint16 &d0, simd16uint16 &d1)

inline int64_t adjust_id(size_t b, size_t j)

inline uint32_t get_lt_mask(uint16_t thr, size_t b, simd16uint16 d0, simd16uint16 d1)

return binary mask of elements below thr in (d0, d1) inverse_test returns elements above

Public Members

RangeSearchPartialResult &pres

size_t q0

std::vector<Triplet> triplets

std::vector<size_t> n_per_query

RangeSearchResult &rres

float radius

std::vector<uint16_t> thresholds

bool disable = false

int64_t i0 = 0

int64_t j0 = 0

const IDSelector *sel

size_t nq

size_t ntotal

const idx_t *id_map = nullptr

these fields are used mainly for the IVF variants (with_id_map=true)

const int *q_map = nullptr

const uint16_t *dbias = nullptr

const float *normalizers = nullptr

bool is_CMax = false

uint8_t sizeof_ids = 0

bool with_fields = false