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faiss Namespace Reference

## Classes
struct | AutoTuneCriterion
struct | OneRecallAtRCriterion
struct | IntersectionCriterion
struct | OperatingPoint
struct | OperatingPoints
struct | ParameterRange
| possible values of a parameter, sorted from least to most expensive/accurate More...
struct | ParameterSpace
struct | RangeSearchResult
struct | IDSelector
struct | IDSelectorRange
struct | IDSelectorBatch
struct | BufferList
struct | RangeSearchPartialResult
| the entries in the buffers are split per query More...
struct | ClusteringParameters
struct | Clustering
class | FaissException
| Base class for Faiss exceptions. More...
struct | ScopeDeleter
struct | ScopeDeleter1
struct | HammingComputer4
struct | HammingComputer8
struct | HammingComputer16
struct | HammingComputer20
struct | HammingComputer32
struct | HammingComputer64
struct | HammingComputerDefault
struct | HammingComputerM8
struct | HammingComputerM4
struct | HammingComputer
struct | GenHammingComputer8
struct | GenHammingComputer16
struct | GenHammingComputer32
struct | GenHammingComputerM8
struct | CMax
struct | CMin
struct | HeapArray
struct | Index
struct | ScopeFileCloser
struct | Cloner
struct | IndexFlat
struct | IndexFlatIP
struct | IndexFlatL2
struct | IndexFlatL2BaseShift
struct | IndexRefineFlat
struct | IndexFlat1D
| optimized version for 1D "vectors" More...
struct | VisitedTable
| set implementation optimized for fast access. More...
struct | GenericDistanceComputer
struct | FlatL2Dis
struct | PQDis
struct | SQDis
struct | Distance2Level
struct | DistanceXPQ4
struct | Distance2xXPQ4
struct | HNSW
struct | HNSWStats
struct | ReconstructFromNeighbors
struct | IndexHNSW
struct | IndexHNSWFlat
struct | IndexHNSWPQ
struct | IndexHNSWSQ
struct | IndexHNSW2Level
struct | Level1Quantizer
struct | InvertedLists
struct | ArrayInvertedLists
struct | IndexIVF
struct | IndexIVFStats
struct | IndexIVFFlat
struct | CodeCmp
struct | IndexIVFPQ
struct | IndexIVFPQStats
struct | IndexIVFPQR
struct | Index2Layer
struct | IndexLSH
struct | IndexPQ
struct | IndexPQStats
struct | MultiIndexQuantizer
struct | MultiIndexQuantizer2
struct | ScalarQuantizer
struct | IndexScalarQuantizer
struct | IndexIVFScalarQuantizer
struct | IndexIDMap
struct | IndexIDMap2
struct | IndexShards
struct | IndexSplitVectors
struct | LockLevels
struct | OnDiskInvertedLists
struct | Score3Computer
struct | IndirectSort
struct | RankingScore2
struct | SimulatedAnnealingParameters
| parameters used for the simulated annealing method More...
struct | PermutationObjective
| abstract class for the loss function More...
struct | ReproduceDistancesObjective
struct | SimulatedAnnealingOptimizer
| Simulated annealing optimization algorithm for permutations. More...
struct | PolysemousTraining
| optimizes the order of indices in a ProductQuantizer More...
struct | ProductQuantizer
struct | NopDistanceCorrection
struct | BaseShiftDistanceCorrection
struct | RandomGenerator
| random generator that can be used in multithreaded contexts More...
struct | VectorTransform
struct | LinearTransform
struct | RandomRotationMatrix
| Randomly rotate a set of vectors. More...
struct | PCAMatrix
struct | OPQMatrix
struct | RemapDimensionsTransform
struct | NormalizationTransform
struct | IndexPreTransform

## Typedefs
typedef HeapArray< CMin< float, long > > | float_minheap_array_t
typedef HeapArray< CMin< int, long > > | int_minheap_array_t
typedef HeapArray< CMax< float, long > > | float_maxheap_array_t
typedef HeapArray< CMax< int, long > > | int_maxheap_array_t

## Enumerations
enum | MetricType { METRIC_INNER_PRODUCT = 0, METRIC_L2 = 1 }
| Some algorithms support both an inner product version and a L2 search version.

## Functions
Index * | index_factory (int d, const char *description_in, MetricType metric)
float | kmeans_clustering (size_t d, size_t n, size_t k, const float *x, float *centroids)
template<size_t nbits, typename T >
T | hamming (const uint8_t *bs1, const uint8_t *bs2)
template<size_t nbits>
hamdis_t | hamming (const uint64_t *bs1, const uint64_t *bs2)
template<>
hamdis_t | hamming< 64 > (const uint64_t *pa, const uint64_t *pb)
template<>
hamdis_t | hamming< 128 > (const uint64_t *pa, const uint64_t *pb)
template<>
hamdis_t | hamming< 256 > (const uint64_t *pa, const uint64_t *pb)
hamdis_t | hamming (const uint64_t *bs1, const uint64_t *bs2, size_t nwords)
template<size_t nbits>
void | hammings (const uint64_t *bs1, const uint64_t *bs2, size_t n1, size_t n2, hamdis_t *dis)
void | hammings (const uint64_t *bs1, const uint64_t *bs2, size_t n1, size_t n2, size_t nwords, hamdis_t *__restrict dis)
template<size_t nbits>
void | hamming_count_thres (const uint64_t *bs1, const uint64_t *bs2, size_t n1, size_t n2, hamdis_t ht, size_t *nptr)
template<size_t nbits>
void | crosshamming_count_thres (const uint64_t *dbs, size_t n, int ht, size_t *nptr)
template<size_t nbits>
size_t | match_hamming_thres (const uint64_t *bs1, const uint64_t *bs2, size_t n1, size_t n2, int ht, long *idx, hamdis_t *hams)
void | fvec2bitvec (const float *x, uint8_t *b, size_t d)
void | fvecs2bitvecs (const float *x, uint8_t *b, size_t d, size_t n)
void | bitvec_print (const uint8_t *b, size_t d)
void | hammings (const uint8_t *a, const uint8_t *b, size_t na, size_t nb, size_t ncodes, hamdis_t *__restrict dis)
void | hammings_knn_core (int_maxheap_array_t *ha, const uint8_t *a, const uint8_t *b, size_t nb, size_t ncodes)
void | hammings_knn (int_maxheap_array_t *ha, const uint8_t *a, const uint8_t *b, size_t nb, size_t ncodes, int order)
void | hamming_count_thres (const uint8_t *bs1, const uint8_t *bs2, size_t n1, size_t n2, hamdis_t ht, size_t ncodes, size_t *nptr)
void | crosshamming_count_thres (const uint8_t *dbs, size_t n, hamdis_t ht, size_t ncodes, size_t *nptr)
size_t | match_hamming_thres (const uint8_t *bs1, const uint8_t *bs2, size_t n1, size_t n2, hamdis_t ht, size_t ncodes, long *idx, hamdis_t *dis)
void | generalized_hammings_knn (int_maxheap_array_t *ha, const uint8_t *a, const uint8_t *b, size_t nb, size_t code_size, int ordered)
int | popcount64 (uint64_t x)
void | hammings (const uint8_t *a, const uint8_t *b, size_t na, size_t nb, size_t nbytespercode, hamdis_t *dis)
| SPECIALIZED_HC (4)
| SPECIALIZED_HC (8)
| SPECIALIZED_HC (16)
| SPECIALIZED_HC (20)
| SPECIALIZED_HC (32)
| SPECIALIZED_HC (64)
int | generalized_hamming_64 (uint64_t a)
template<class C >
void | heap_pop (size_t k, typename C::T *bh_val, typename C::TI *bh_ids)
template<class C >
void | heap_push (size_t k, typename C::T *bh_val, typename C::TI *bh_ids, typename C::T val, typename C::TI ids)
template<typename T >
void | minheap_pop (size_t k, T *bh_val, long *bh_ids)
template<typename T >
void | minheap_push (size_t k, T *bh_val, long *bh_ids, T val, long ids)
template<typename T >
void | maxheap_pop (size_t k, T *bh_val, long *bh_ids)
template<typename T >
void | maxheap_push (size_t k, T *bh_val, long *bh_ids, T val, long ids)
template<class C >
void | heap_heapify (size_t k, typename C::T *bh_val, typename C::TI *bh_ids, const typename C::T *x=nullptr, const typename C::TI *ids=nullptr, size_t k0=0)
template<typename T >
void | minheap_heapify (size_t k, T *bh_val, long *bh_ids, const T *x=nullptr, const long *ids=nullptr, size_t k0=0)
template<typename T >
void | maxheap_heapify (size_t k, T *bh_val, long *bh_ids, const T *x=nullptr, const long *ids=nullptr, size_t k0=0)
template<class C >
void | heap_addn (size_t k, typename C::T *bh_val, typename C::TI *bh_ids, const typename C::T *x, const typename C::TI *ids, size_t n)
template<typename T >
void | minheap_addn (size_t k, T *bh_val, long *bh_ids, const T *x, const long *ids, size_t n)
template<typename T >
void | maxheap_addn (size_t k, T *bh_val, long *bh_ids, const T *x, const long *ids, size_t n)
template<typename C >
size_t | heap_reorder (size_t k, typename C::T *bh_val, typename C::TI *bh_ids)
template<typename T >
size_t | minheap_reorder (size_t k, T *bh_val, long *bh_ids)
template<typename T >
size_t | maxheap_reorder (size_t k, T *bh_val, long *bh_ids)
template<class C >
void | indirect_heap_pop (size_t k, const typename C::T *bh_val, typename C::TI *bh_ids)
template<class C >
void | indirect_heap_push (size_t k, const typename C::T *bh_val, typename C::TI *bh_ids, typename C::TI id)
void | write_VectorTransform (const VectorTransform *vt, FILE *f)
void | write_ProductQuantizer (const ProductQuantizer *pq, const char *fname)
void | write_index (const Index *idx, FILE *f)
void | write_index (const Index *idx, const char *fname)
void | write_VectorTransform (const VectorTransform *vt, const char *fname)
VectorTransform * | read_VectorTransform (FILE *f)
InvertedLists * | read_InvertedLists (FILE *f, int io_flags)
ProductQuantizer * | read_ProductQuantizer (const char *fname)
Index * | read_index (FILE *f, int io_flags)
Index * | read_index (const char *fname, int io_flags)
VectorTransform * | read_VectorTransform (const char *fname)
Index * | clone_index (const Index *index)
template<typename CT , class C >
void | pq_estimators_from_tables_Mmul4 (int M, const CT *codes, size_t ncodes, const float *__restrict dis_table, size_t ksub, size_t k, float *heap_dis, long *heap_ids)
template<typename CT , class C >
void | pq_estimators_from_tables_M4 (const CT *codes, size_t ncodes, const float *__restrict dis_table, size_t ksub, size_t k, float *heap_dis, long *heap_ids)
void | merge_into (Index *index0, Index *index1, bool shift_ids)
double | getmillisecs ()
| ms elapsed since some arbitrary epoch
void | float_rand (float *x, size_t n, long seed)
void | float_randn (float *x, size_t n, long seed)
void | long_rand (long *x, size_t n, long seed)
void | rand_perm (int *perm, size_t n, long seed)
void | byte_rand (uint8_t *x, size_t n, long seed)
void | reflection (const float *__restrict u, float *__restrict x, size_t n, size_t d, size_t nu)
void | reflection_ref (const float *u, float *x, size_t n, size_t d, size_t nu)
float | fvec_L2sqr_ref (const float *x, const float *y, size_t d)
float | fvec_inner_product_ref (const float *x, const float *y, size_t d)
float | fvec_norm_L2sqr_ref (const float *__restrict x, size_t d)
float | fvec_L2sqr (const float *x, const float *y, size_t d)
| Squared L2 distance between two vectors.
float | fvec_inner_product (const float *x, const float *y, size_t d)
float | fvec_norm_L2sqr (const float *x, size_t d)
void | fvec_inner_products_ny (float *__restrict ip, const float *x, const float *y, size_t d, size_t ny)
void | fvec_L2sqr_ny (float *__restrict dis, const float *x, const float *y, size_t d, size_t ny)
void | fvec_norms_L2 (float *__restrict nr, const float *__restrict x, size_t d, size_t nx)
void | fvec_norms_L2sqr (float *__restrict nr, const float *__restrict x, size_t d, size_t nx)
void | fvec_renorm_L2 (size_t d, size_t nx, float *__restrict x)
void | knn_inner_product (const float *x, const float *y, size_t d, size_t nx, size_t ny, float_minheap_array_t *res)
void | knn_L2sqr (const float *x, const float *y, size_t d, size_t nx, size_t ny, float_maxheap_array_t *res)
void | knn_L2sqr_base_shift (const float *x, const float *y, size_t d, size_t nx, size_t ny, float_maxheap_array_t *res, const float *base_shift)
void | fvec_inner_products_by_idx (float *__restrict ip, const float *x, const float *y, const long *__restrict ids, size_t d, size_t nx, size_t ny)
void | fvec_L2sqr_by_idx (float *__restrict dis, const float *x, const float *y, const long *__restrict ids, size_t d, size_t nx, size_t ny)
void | knn_inner_products_by_idx (const float *x, const float *y, const long *ids, size_t d, size_t nx, size_t ny, float_minheap_array_t *res)
void | knn_L2sqr_by_idx (const float *x, const float *y, const long *__restrict ids, size_t d, size_t nx, size_t ny, float_maxheap_array_t *res)
void | range_search_L2sqr (const float *x, const float *y, size_t d, size_t nx, size_t ny, float radius, RangeSearchResult *res)
void | range_search_inner_product (const float *x, const float *y, size_t d, size_t nx, size_t ny, float radius, RangeSearchResult *result)
| same as range_search_L2sqr for the inner product similarity
void | inner_product_to_L2sqr (float *__restrict dis, const float *nr1, const float *nr2, size_t n1, size_t n2)
void | matrix_qr (int m, int n, float *a)
void | pairwise_L2sqr (long d, long nq, const float *xq, long nb, const float *xb, float *dis, long ldq, long ldb, long ldd)
int | km_update_centroids (const float *x, float *centroids, long *assign, size_t d, size_t k, size_t n, size_t k_frozen)
void | ranklist_handle_ties (int k, long *idx, const float *dis)
size_t | merge_result_table_with (size_t n, size_t k, long *I0, float *D0, const long *I1, const float *D1, bool keep_min, long translation)
size_t | ranklist_intersection_size (size_t k1, const long *v1, size_t k2, const long *v2_in)
double | imbalance_factor (int k, const int *hist)
| same, takes a histogram as input
double | imbalance_factor (int n, int k, const long *assign)
| a balanced assignment has a IF of 1
int | ivec_hist (size_t n, const int *v, int vmax, int *hist)
| compute histogram on v
void | bincode_hist (size_t n, size_t nbits, const uint8_t *codes, int *hist)
size_t | ivec_checksum (size_t n, const int *a)
| compute a checksum on a table.
void | fvec_argsort (size_t n, const float *vals, size_t *perm)
void | fvec_argsort_parallel (size_t n, const float *vals, size_t *perm)
void | fvec_madd (size_t n, const float *a, float bf, const float *b, float *c)
int | fvec_madd_and_argmin (size_t n, const float *a, float bf, const float *b, float *c)
const float * | fvecs_maybe_subsample (size_t d, size_t *n, size_t nmax, const float *x, bool verbose, long seed)
size_t | get_mem_usage_kb ()
| get current RSS usage in kB
void | fvec_inner_products_ny (float *ip, const float *x, const float *y, size_t d, size_t ny)
void | fvec_norms_L2 (float *ip, const float *x, size_t d, size_t nx)
void | fvec_norms_L2sqr (float *ip, const float *x, size_t d, size_t nx)
| same as fvec_norms_L2, but computes square norms
void | fvec_renorm_L2 (size_t d, size_t nx, float *x)
void | reflection (const float *u, float *x, size_t n, size_t d, size_t nu)

## Variables
int | read_old_fmt_hack = 0
const int | IO_FLAG_MMAP = 1
const int | IO_FLAG_READ_ONLY = 2
HNSWStats | hnsw_stats
IndexIVFStats | indexIVF_stats
IndexIVFPQStats | indexIVFPQ_stats
IndexPQStats | indexPQ_stats
int | distance_compute_blas_threshold = 20

## Detailed Description

Copyright (c) 2015-present, Facebook, Inc. All rights reserved.

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

Copyright (c) 2015-present, Facebook, Inc. All rights reserved.

This source code is licensed under the BSD+Patents license found in the LICENSE file in the root directory of this source tree.Multi-dimensional array class for CUDA device and host usage. Originally from Facebook's fbcunn, since added to the Torch GPU library cutorch as well.

Copyright (c) 2015-present, Facebook, Inc. All rights reserved.

This source code is licensed under the BSD+Patents 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) 2015-present, Facebook, Inc. All rights reserved.

This source code is licensed under the BSD+Patents license found in the LICENSE file in the root directory of this source tree. Copyright 2004-present Facebook. All Rights Reserved -*- c++ -*-

A few utilitary functions for similarity search:

- random generators
- optimized exhaustive distance and knn search functions
- some functions reimplemented from torch for speed

Copyright (c) 2015-present, Facebook, Inc. All rights reserved.

This source code is licensed under the BSD+Patents 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.

## Function Documentation

void faiss::bincode_hist | ( | size_t | n,
|  | size_t | nbits,
|  | const uint8_t * | codes,
|  | int * | hist
| ) |  |

Compute histogram of bits on a code array

Parameters

  codes | size(n, nbits / 8)
  hist | size(nbits): nb of 1s in the array of codes

Definition at line 1649 of file utils.cpp.

void faiss::fvec_madd | ( | size_t | n,
|  | const float * | a,
|  | float | bf,
|  | const float * | b,
|  | float * | c
| ) |  |

compute c := a + bf * b for a, b and c tables

Parameters

  n | size of the tables
  a | size n
  b | size n
  c | restult table, size n

Definition at line 1889 of file utils.cpp.

int faiss::fvec_madd_and_argmin | ( | size_t | n,
|  | const float * | a,
|  | float | bf,
|  | const float * | b,
|  | float * | c
| ) |  |

same as fvec_madd, also return index of the min of the result table

Returns
  index of the min of table c

Definition at line 1963 of file utils.cpp.

float faiss::fvec_norm_L2sqr | ( | const float * | x,
|  | size_t | d
| ) |  |

squared norm of a vector

Definition at line 632 of file utils.cpp.

void faiss::fvec_norms_L2 | ( | float * | ip,
|  | const float * | x,
|  | size_t | d,
|  | size_t | nx
| ) |  |

compute the L2 norms for a set of vectors

Parameters

  ip | output norms, size nx
  x | set of vectors, size nx * d

const float * faiss::fvecs_maybe_subsample | ( | size_t | d,
|  | size_t * | n,
|  | size_t | nmax,
|  | const float * | x,
|  | bool | verbose = `false`,
|  | long | seed = `1234`
| ) |  |

random subsamples a set of vectors if there are too many of them

Parameters

  d | dimension of the vectors
  n | on input: nb of input vectors, output: nb of output vectors
  nmax | max nb of vectors to keep
  x | input array, size *n-by-d
  seed | random seed to use for sampling

Returns
  x or an array allocated with new [] with *n vectors

Definition at line 1975 of file utils.cpp.

void faiss::generalized_hammings_knn | ( | int_maxheap_array_t * | ha,
|  | const uint8_t * | a,
|  | const uint8_t * | b,
|  | size_t | nb,
|  | size_t | code_size,
|  | int | ordered = `true`
| ) |  |

generalized Hamming distances (= count number of code bytes that are the same)

Definition at line 639 of file hamming.cpp.

void faiss::hammings | ( | const uint8_t * | a,
|  | const uint8_t * | b,
|  | size_t | na,
|  | size_t | nb,
|  | size_t | nbytespercode,
|  | hamdis_t * | dis
| ) |  |

Compute a set of Hamming distances between na and nb binary vectors

Parameters

  a | size na * nbytespercode
  b | size nb * nbytespercode
  nbytespercode | should be multiple of 8
  dis | output distances, size na * nb

void faiss::hammings_knn | ( | int_maxheap_array_t * | ha,
|  | const uint8_t * | a,
|  | const uint8_t * | b,
|  | size_t | nb,
|  | size_t | ncodes,
|  | int | ordered
| ) |  |

Return the k smallest Hamming distances for a set of binary query vectors

Parameters

  a | queries, size ha->nh * ncodes
  b | database, size nb * ncodes
  nb | number of database vectors
  ncodes | size of the binary codes (bytes)
  ordered | if != 0: order the results by decreasing distance (may be bottleneck for k/n > 0.01)

Definition at line 474 of file hamming.cpp.

template<class C >

void faiss::heap_pop | ( | size_t | k,
|  | typename C::T * | bh_val,
|  | typename C::TI * | bh_ids
| ) |  |
| inline

Pops the top element from the heap defined by bh_val[0..k-1] and bh_ids[0..k-1]. on output the element at k-1 is undefined.

Definition at line 90 of file Heap.h.

template<class C >

void faiss::heap_push | ( | size_t | k,
|  | typename C::T * | bh_val,
|  | typename C::TI * | bh_ids,
|  | typename C::T | val,
|  | typename C::TI | ids
| ) |  |
| inline

Pushes the element (val, ids) into the heap bh_val[0..k-2] and bh_ids[0..k-2]. on output the element at k-1 is defined.

Definition at line 126 of file Heap.h.

Index * faiss::index_factory | ( | int | d,
|  | const char * | description,
|  | MetricType | metric = `METRIC_L2`
| ) |  |

Build and index with the sequence of processing steps described in the string.

Definition at line 688 of file AutoTune.cpp.

int faiss::km_update_centroids | ( | const float * | x,
|  | float * | centroids,
|  | long * | assign,
|  | size_t | d,
|  | size_t | k,
|  | size_t | n,
|  | size_t | k_frozen
| ) |  |

For k-means: update stage.

Parameters

  x | training vectors, size n * d
  centroids | centroid vectors, size k * d
  assign | nearest centroid for each training vector, size n
  k_frozen | do not update the k_frozen first centroids

Returns
  nb of spliting operations to fight empty clusters

Definition at line 1401 of file utils.cpp.

float faiss::kmeans_clustering | ( | size_t | d,
|  | size_t | n,
|  | size_t | k,
|  | const float * | x,
|  | float * | centroids
| ) |  |

simplified interface

Parameters

  d | dimension of the data
  n | nb of training vectors
  k | nb of output centroids
  x | training set (size n * d)
  centroids | output centroids (size k * d)

Returns
  final quantization error

Definition at line 241 of file Clustering.cpp.

void faiss::knn_inner_product | ( | const float * | x,
|  | const float * | y,
|  | size_t | d,
|  | size_t | nx,
|  | size_t | ny,
|  | float_minheap_array_t * | res
| ) |  |

Return the k nearest neighors of each of the nx vectors x among the ny vector y, w.r.t to max inner product

Parameters

  x | query vectors, size nx * d
  y | database vectors, size ny * d
  res | result array, which also provides k. Sorted on output

Definition at line 948 of file utils.cpp.

void faiss::knn_L2sqr | ( | const float * | x,
|  | const float * | y,
|  | size_t | d,
|  | size_t | nx,
|  | size_t | ny,
|  | float_maxheap_array_t * | res
| ) |  |

Same as knn_inner_product, for the L2 distance

Definition at line 968 of file utils.cpp.

void faiss::knn_L2sqr_base_shift | ( | const float * | x,
|  | const float * | y,
|  | size_t | d,
|  | size_t | nx,
|  | size_t | ny,
|  | float_maxheap_array_t * | res,
|  | const float * | base_shift
| ) |  |

same as knn_L2sqr, but base_shift[bno] is subtracted to all computed distances.

Parameters

  base_shift | size ny

Definition at line 988 of file utils.cpp.

void faiss::matrix_qr | ( | int | m,
|  | int | n,
|  | float * | a
| ) |  |

compute the Q of the QR decomposition for m > n

Parameters

  a | size n * m: input matrix and output Q

Definition at line 1322 of file utils.cpp.

size_t faiss::merge_result_table_with | ( | size_t | n,
|  | size_t | k,
|  | long * | I0,
|  | float * | D0,
|  | const long * | I1,
|  | const float * | D1,
|  | bool | keep_min = `true`,
|  | long | translation = `0`
| ) |  |

merge a result table into another one

Parameters

  I0,D0 | first result table, size (n, k)
  I1,D1 | second result table, size (n, k)
  keep_min | if true, keep min values, otherwise keep max
  translation | add this value to all I1's indexes

Returns
  nb of values that were taken from the second table

Definition at line 1511 of file utils.cpp.

void faiss::pairwise_L2sqr | ( | long | d,
|  | long | nq,
|  | const float * | xq,
|  | long | nb,
|  | const float * | xb,
|  | float * | dis,
|  | long | ldq = `-1`,
|  | long | ldb = `-1`,
|  | long | ldd = `-1`
| ) |  |

Compute pairwise distances between sets of vectors

Parameters

  d | dimension of the vectors
  nq | nb of query vectors
  nb | nb of database vectors
  xq | query vectors (size nq * d)
  xb | database vectros (size nb * d)
  dis | output distances (size nq * nb)
  ldq,ldb,ldd | strides for the matrices

Definition at line 1344 of file utils.cpp.

void faiss::range_search_L2sqr | ( | const float * | x,
|  | const float * | y,
|  | size_t | d,
|  | size_t | nx,
|  | size_t | ny,
|  | float | radius,
|  | RangeSearchResult * | result
| ) |  |

Return the k nearest neighors of each of the nx vectors x among the ny vector y, w.r.t to max inner product

Parameters

  x | query vectors, size nx * d
  y | database vectors, size ny * d
  radius | search radius around the x vectors
  result | result structure

Definition at line 1267 of file utils.cpp.

void faiss::ranklist_handle_ties | ( | int | k,
|  | long * | idx,
|  | const float * | dis
| ) |  |

distances are supposed to be sorted. Sorts indices with same distance

Definition at line 1495 of file utils.cpp.

size_t faiss::ranklist_intersection_size | ( | size_t | k1,
|  | const long * | v1,
|  | size_t | k2,
|  | const long * | v2
| ) |  |

count the number of comon elements between v1 and v2 algorithm = sorting + bissection to avoid double-counting duplicates

Definition at line 1576 of file utils.cpp.