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/data/users/matthijs/github_faiss/faiss/utils.h
/**
* Copyright (c) 2015-present, Facebook, Inc.
* All rights reserved.
*
* This source code is licensed under the CC-by-NC 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
*/
#ifndef FAISS_utils_h
#define FAISS_utils_h
#include <stdint.h>
// for the random data struct
#include <cstdlib>
#include "Heap.h"
namespace faiss {
/**************************************************
* Get some stats about the system
**************************************************/
/// ms elapsed since some arbitrary epoch
double getmillisecs ();
/// get current RSS usage in kB
size_t get_mem_usage_kb ();
/**************************************************
* Random data generation functions
**************************************************/
/// random generator that can be used in multithreaded contexts
struct RandomGenerator {
#ifdef __linux__
char rand_state [8];
struct random_data rand_data;
#elif __APPLE__
unsigned rand_state;
#endif
/// random 31-bit positive integer
int rand_int ();
/// random long < 2 ^ 62
long rand_long ();
/// generate random number between 0 and max-1
int rand_int (int max);
/// between 0 and 1
float rand_float ();
double rand_double ();
/// initialize
explicit RandomGenerator (long seed = 1234);
/// default copy constructor messes up pointer in rand_data
RandomGenerator (const RandomGenerator & other);
};
/* Generate an array of uniform random floats / multi-threaded implementation */
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 byte_rand (uint8_t * x, size_t n, long seed);
/* random permutation */
void rand_perm (int * perm, size_t n, long seed);
/*********************************************************
* Optimized distance/norm/inner prod computations
*********************************************************/
/// Squared L2 distance between two vectors
float fvec_L2sqr (
const float * x,
const float * y,
size_t d);
/* SSE-implementation of inner product and L2 distance */
float fvec_inner_product (
const float * x,
const float * y,
size_t d);
/// a balanced assignment has a IF of 1
double imbalance_factor (int n, int k, const long *assign);
/// same, takes a histogram as input
double imbalance_factor (int k, const int *hist);
/** Compute pairwise distances between sets of vectors
*
* @param d dimension of the vectors
* @param nq nb of query vectors
* @param nb nb of database vectors
* @param xq query vectors (size nq * d)
* @param xb database vectros (size nb * d)
* @param dis output distances (size nq * nb)
* @param ldq,ldb, ldd strides for the matrices
*/
void 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 the inner product between nx vectors x and one y */
void fvec_inner_products_ny (
float * ip, /* output inner product */
const float * x,
const float * y,
size_t d, size_t ny);
/* compute ny square L2 distance bewteen x and a set of contiguous y vectors */
void fvec_L2sqr_ny (
float * __restrict dis,
const float * x,
const float * y,
size_t d, size_t ny);
/** squared norm of a vector */
float fvec_norm_L2sqr (const float * x,
size_t d);
/** compute the L2 norms for a set of vectors
*
* @param ip output norms, size nx
* @param x set of vectors, size nx * d
*/
void fvec_norms_L2 (float * ip, const float * x, size_t d, size_t nx);
/// same as fvec_norms_L2, but computes square norms
void fvec_norms_L2sqr (float * ip, const float * x, size_t d, size_t nx);
/* L2-renormalize a set of vector. Nothing done if the vector is 0-normed */
void fvec_renorm_L2 (size_t d, size_t nx, float * x);
/* This function exists because the Torch counterpart is extremly slow
(not multi-threaded + unexpected overhead even in single thread).
It is here to implement the usual property |x-y|^2=|x|^2+|y|^2-2<x|y> */
void inner_product_to_L2sqr (float * __restrict dis,
const float * nr1,
const float * nr2,
size_t n1, size_t n2);
/***************************************************************************
* Compute a subset of distances
***************************************************************************/
/* compute the inner product between x and a subset y of ny vectors,
whose indices are given by idy. */
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);
/* same but for a subset in y indexed by idsy (ny vectors in total) */
void fvec_L2sqr_by_idx (
float * __restrict dis,
const float * x,
const float * y,
const long * __restrict ids, /* ids of y vecs */
size_t d, size_t nx, size_t ny);
/***************************************************************************
* KNN functions
***************************************************************************/
/** Return the k nearest neighors of each of the nx vectors x among the ny
* vector y, w.r.t to max inner product
*
* @param x query vectors, size nx * d
* @param y database vectors, size ny * d
* @param res result array, which also provides k. Sorted on output
*/
void knn_inner_product (
const float * x,
const float * y,
size_t d, size_t nx, size_t ny,
float_minheap_array_t * res);
/** Same as knn_inner_product, for the L2 distance */
void 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_L2sqr, but base_shift[bno] is subtracted to all
* computed distances.
*
* @param base_shift size ny
*/
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);
/* Find the nearest neighbors for nx queries in a set of ny vectors
* indexed by ids. May be useful for re-ranking a pre-selected vector list
*/
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);
/***************************************************************************
* Range search
***************************************************************************/
/// Forward declaration, see AuxIndexStructures.h
struct RangeSearchResult;
/** Return the k nearest neighors of each of the nx vectors x among the ny
* vector y, w.r.t to max inner product
*
* @param x query vectors, size nx * d
* @param y database vectors, size ny * d
* @param radius search radius around the x vectors
* @param result result structure
*/
void range_search_L2sqr (
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 range_search_inner_product (
const float * x,
const float * y,
size_t d, size_t nx, size_t ny,
float radius,
RangeSearchResult *result);
/***************************************************************************
* Misc matrix and vector manipulation functions
***************************************************************************/
/** compute c := a + bf * b for a, b and c tables
*
* @param n size of the tables
* @param a size n
* @param b size n
* @param c restult table, size n
*/
void fvec_madd (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
* @return index of the min of table c
*/
int fvec_madd_and_argmin (size_t n, const float *a,
float bf, const float *b, float *c);
/* perform a reflection (not an efficient implementation, just for test ) */
void reflection (const float * u, float * x, size_t n, size_t d, size_t nu);
/** For k-means: update stage. Returns nb of split clusters. */
int km_update_centroids (
const float * x,
float * centroids,
long * assign,
size_t d, size_t k, size_t n);
/** compute the Q of the QR decomposition for m > n
* @param a size n * m: input matrix and output Q
*/
void matrix_qr (int m, int n, float *a);
/** distances are supposed to be sorted. Sorts indices with same distance*/
void ranklist_handle_ties (int k, long *idx, const float *dis);
/** count the number of comon elements between v1 and v2
* algorithm = sorting + bissection to avoid double-counting duplicates
*/
size_t ranklist_intersection_size (size_t k1, const long *v1,
size_t k2, const long *v2);
/** merge a result table into another one
*
* @param I0, D0 first result table, size (n, k)
* @param I1, D1 second result table, size (n, k)
* @param keep_min if true, keep min values, otherwise keep max
* @param translation add this value to all I1's indexes
* @return nb of values that were taken from the second table
*/
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 = true,
long translation = 0);
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);
/// compute histogram on v
int ivec_hist (size_t n, const int * v, int vmax, int *hist);
/** Compute histogram of bits on a code array
*
* @param codes size(n, nbits / 8)
* @param hist size(nbits): nb of 1s in the array of codes
*/
void bincode_hist(size_t n, size_t nbits, const uint8_t *codes, int *hist);
/// compute a checksum on a table.
size_t ivec_checksum (size_t n, const int *a);
/** random subsamples a set of vectors if there are too many of them
*
* @param d dimension of the vectors
* @param n on input: nb of input vectors, output: nb of output vectors
* @param nmax max nb of vectors to keep
* @param x input array, size *n-by-d
* @param seed random seed to use for sampling
* @return x or an array allocated with new [] with *n vectors
*/
const float *fvecs_maybe_subsample (
size_t d, size_t *n, size_t nmax, const float *x,
bool verbose = false, long seed = 1234);
} // namspace faiss
#endif /* FAISS_utils_h */
faiss::RandomGenerator
random generator that can be used in multithreaded contexts
Definition: utils.h:48
faiss::knn_L2sqr_base_shift
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)
Definition: utils.cpp:955
faiss::RandomGenerator::RandomGenerator
RandomGenerator(long seed=1234)
initialize
faiss::km_update_centroids
int km_update_centroids(const float *x, float *centroids, long *assign, size_t d, size_t k, size_t n)
Definition: utils.cpp:1369
faiss::fvec_L2sqr
float fvec_L2sqr(const float *x, const float *y, size_t d)
Squared L2 distance between two vectors.
Definition: utils.cpp:481
faiss::bincode_hist
void bincode_hist(size_t n, size_t nbits, const uint8_t *codes, int *hist)
Definition: utils.cpp:1615
faiss::fvecs_maybe_subsample
const float * fvecs_maybe_subsample(size_t d, size_t *n, size_t nmax, const float *x, bool verbose, long seed)
Definition: utils.cpp:1941
faiss::ranklist_handle_ties
void ranklist_handle_ties(int k, long *idx, const float *dis)
Definition: utils.cpp:1461
faiss::RandomGenerator::rand_float
float rand_float()
between 0 and 1
Definition: utils.cpp:207
faiss::fvec_madd
void fvec_madd(size_t n, const float *a, float bf, const float *b, float *c)
Definition: utils.cpp:1855
faiss::get_mem_usage_kb
size_t get_mem_usage_kb()
get current RSS usage in kB
faiss::ivec_hist
int ivec_hist(size_t n, const int *v, int vmax, int *hist)
compute histogram on v
Definition: utils.cpp:1604
faiss::RandomGenerator::rand_long
long rand_long()
random long &lt; 2 ^ 62
faiss::merge_result_table_with
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)
Definition: utils.cpp:1477
faiss::RandomGenerator::rand_int
int rand_int()
random 31-bit positive integer
faiss::HeapArray
Definition: Heap.h:350
faiss::ranklist_intersection_size
size_t ranklist_intersection_size(size_t k1, const long *v1, size_t k2, const long *v2_in)
Definition: utils.cpp:1542
faiss::pairwise_L2sqr
void pairwise_L2sqr(long d, long nq, const float *xq, long nb, const float *xb, float *dis, long ldq, long ldb, long ldd)
Definition: utils.cpp:1311
faiss::range_search_inner_product
void range_search_inner_product(const float *x, const float *y, size_t d, size_t nx, size_t ny, float radius, RangeSearchResult *res)
same as range_search_L2sqr for the inner product similarity
Definition: utils.cpp:1249
faiss::knn_inner_product
void knn_inner_product(const float *x, const float *y, size_t d, size_t nx, size_t ny, float_minheap_array_t *res)
Definition: utils.cpp:915
faiss::getmillisecs
double getmillisecs()
ms elapsed since some arbitrary epoch
Definition: utils.cpp:70
faiss::imbalance_factor
double imbalance_factor(int k, const int *hist)
same, takes a histogram as input
Definition: utils.cpp:1580
faiss::fvec_norm_L2sqr
float fvec_norm_L2sqr(const float *x, size_t d)
Definition: utils.cpp:538
faiss::range_search_L2sqr
void range_search_L2sqr(const float *x, const float *y, size_t d, size_t nx, size_t ny, float radius, RangeSearchResult *res)
Definition: utils.cpp:1234
faiss::matrix_qr
void matrix_qr(int m, int n, float *a)
Definition: utils.cpp:1289
faiss::RangeSearchResult
Definition: AuxIndexStructures.h:29
faiss::ivec_checksum
size_t ivec_checksum(size_t n, const int *a)
compute a checksum on a table.
Definition: utils.cpp:1638
faiss::fvec_madd_and_argmin
int fvec_madd_and_argmin(size_t n, const float *a, float bf, const float *b, float *c)
Definition: utils.cpp:1929
faiss::knn_L2sqr
void knn_L2sqr(const float *x, const float *y, size_t d, size_t nx, size_t ny, float_maxheap_array_t *res)
Definition: utils.cpp:935