All Classes Namespaces Functions Variables Typedefs Enumerations Enumerator Friends
/tmp/faiss/IndexBinaryIVF.cpp
/**
* 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++ -*-
#include "IndexBinaryIVF.h"
#include <cstdio>
#include <memory>
#include "hamming.h"
#include "utils.h"
#include "AuxIndexStructures.h"
#include "FaissAssert.h"
#include "IndexFlat.h"
namespace faiss {
IndexBinaryIVF::IndexBinaryIVF(IndexBinary *quantizer, size_t d, size_t nlist)
: IndexBinary(d),
invlists(new ArrayInvertedLists(nlist, code_size)),
own_invlists(true),
nprobe(1),
max_codes(0),
maintain_direct_map(false),
quantizer(quantizer),
nlist(nlist),
own_fields(false),
clustering_index(nullptr)
{
FAISS_THROW_IF_NOT (d == quantizer->d);
is_trained = quantizer->is_trained && (quantizer->ntotal == nlist);
cp.niter = 10;
}
IndexBinaryIVF::IndexBinaryIVF()
: invlists(nullptr),
own_invlists(false),
nprobe(1),
max_codes(0),
maintain_direct_map(false),
quantizer(nullptr),
nlist(0),
own_fields(false),
clustering_index(nullptr)
{}
void IndexBinaryIVF::add(idx_t n, const uint8_t *x) {
add_with_ids(n, x, nullptr);
}
void IndexBinaryIVF::add_with_ids(idx_t n, const uint8_t *x, const long *xids) {
add_core(n, x, xids, nullptr);
}
void IndexBinaryIVF::add_core(idx_t n, const uint8_t *x, const long *xids,
const long *precomputed_idx) {
FAISS_THROW_IF_NOT(is_trained);
assert(invlists);
FAISS_THROW_IF_NOT_MSG(!(maintain_direct_map && xids),
"cannot have direct map and add with ids");
const long * idx;
std::unique_ptr<long[]> scoped_idx;
if (precomputed_idx) {
idx = precomputed_idx;
} else {
scoped_idx.reset(new long[n]);
quantizer->assign(n, x, scoped_idx.get());
idx = scoped_idx.get();
}
long n_add = 0;
for (size_t i = 0; i < n; i++) {
long id = xids ? xids[i] : ntotal + i;
long list_no = idx[i];
if (list_no < 0)
continue;
const uint8_t *xi = x + i * code_size;
size_t offset = invlists->add_entry(list_no, id, xi);
if (maintain_direct_map)
direct_map.push_back(list_no << 32 | offset);
n_add++;
}
if (verbose) {
printf("IndexBinaryIVF::add_with_ids: added %ld / %ld vectors\n",
n_add, n);
}
ntotal += n_add;
}
void IndexBinaryIVF::make_direct_map(bool new_maintain_direct_map) {
// nothing to do
if (new_maintain_direct_map == maintain_direct_map)
return;
if (new_maintain_direct_map) {
direct_map.resize(ntotal, -1);
for (size_t key = 0; key < nlist; key++) {
size_t list_size = invlists->list_size(key);
const idx_t *idlist = invlists->get_ids(key);
for (long ofs = 0; ofs < list_size; ofs++) {
FAISS_THROW_IF_NOT_MSG(0 <= idlist[ofs] && idlist[ofs] < ntotal,
"direct map supported only for seuquential ids");
direct_map[idlist[ofs]] = key << 32 | ofs;
}
}
} else {
direct_map.clear();
}
maintain_direct_map = new_maintain_direct_map;
}
void IndexBinaryIVF::search(idx_t n, const uint8_t *x, idx_t k,
int32_t *distances, idx_t *labels) const {
std::unique_ptr<idx_t[]> idx(new idx_t[n * nprobe]);
std::unique_ptr<int32_t[]> coarse_dis(new int32_t[n * nprobe]);
quantizer->search(n, x, nprobe, coarse_dis.get(), idx.get());
invlists->prefetch_lists(idx.get(), n * nprobe);
search_preassigned(n, x, k, idx.get(), coarse_dis.get(),
distances, labels, false);
}
void IndexBinaryIVF::reconstruct(idx_t key, uint8_t *recons) const {
FAISS_THROW_IF_NOT_MSG(direct_map.size() == ntotal,
"direct map is not initialized");
long list_no = direct_map[key] >> 32;
long offset = direct_map[key] & 0xffffffff;
reconstruct_from_offset(list_no, offset, recons);
}
void IndexBinaryIVF::reconstruct_n(idx_t i0, idx_t ni, uint8_t *recons) const {
FAISS_THROW_IF_NOT(ni == 0 || (i0 >= 0 && i0 + ni <= ntotal));
for (long list_no = 0; list_no < nlist; list_no++) {
size_t list_size = invlists->list_size(list_no);
const Index::idx_t *idlist = invlists->get_ids(list_no);
for (long offset = 0; offset < list_size; offset++) {
long id = idlist[offset];
if (!(id >= i0 && id < i0 + ni)) {
continue;
}
uint8_t *reconstructed = recons + (id - i0) * d;
reconstruct_from_offset(list_no, offset, reconstructed);
}
}
}
void IndexBinaryIVF::search_and_reconstruct(idx_t n, const uint8_t *x, idx_t k,
int32_t *distances, idx_t *labels,
uint8_t *recons) const {
std::unique_ptr<idx_t[]> idx(new long[n * nprobe]);
std::unique_ptr<int32_t[]> coarse_dis(new int32_t[n * nprobe]);
quantizer->search(n, x, nprobe, coarse_dis.get(), idx.get());
invlists->prefetch_lists(idx.get(), n * nprobe);
// search_preassigned() with `store_pairs` enabled to obtain the list_no
// and offset into `codes` for reconstruction
search_preassigned(n, x, k, idx.get(), coarse_dis.get(),
distances, labels, /* store_pairs */true);
for (idx_t i = 0; i < n; ++i) {
for (idx_t j = 0; j < k; ++j) {
idx_t ij = i * k + j;
idx_t key = labels[ij];
uint8_t *reconstructed = recons + ij * d;
if (key < 0) {
// Fill with NaNs
memset(reconstructed, -1, sizeof(*reconstructed) * d);
} else {
int list_no = key >> 32;
int offset = key & 0xffffffff;
// Update label to the actual id
labels[ij] = invlists->get_single_id(list_no, offset);
reconstruct_from_offset(list_no, offset, reconstructed);
}
}
}
}
void IndexBinaryIVF::reconstruct_from_offset(long list_no, long offset,
uint8_t *recons) const {
memcpy(recons, invlists->get_single_code(list_no, offset), code_size);
}
void IndexBinaryIVF::reset() {
direct_map.clear();
invlists->reset();
ntotal = 0;
}
long IndexBinaryIVF::remove_ids(const IDSelector& sel) {
FAISS_THROW_IF_NOT_MSG(!maintain_direct_map,
"direct map remove not implemented");
std::vector<long> toremove(nlist);
#pragma omp parallel for
for (long i = 0; i < nlist; i++) {
long l0 = invlists->list_size (i), l = l0, j = 0;
const idx_t *idsi = invlists->get_ids(i);
while (j < l) {
if (sel.is_member(idsi[j])) {
l--;
invlists->update_entry(
i, j,
invlists->get_single_id(i, l),
invlists->get_single_code(i, l));
} else {
j++;
}
}
toremove[i] = l0 - l;
}
// this will not run well in parallel on ondisk because of possible shrinks
long nremove = 0;
for (long i = 0; i < nlist; i++) {
if (toremove[i] > 0) {
nremove += toremove[i];
invlists->resize(
i, invlists->list_size(i) - toremove[i]);
}
}
ntotal -= nremove;
return nremove;
}
void IndexBinaryIVF::train(idx_t n, const uint8_t *x) {
if (verbose)
printf("Training level-1 quantizer\n");
train_q1(n, x, verbose);
is_trained = true;
}
double IndexBinaryIVF::imbalance_factor () const {
std::vector<int> hist(nlist);
for (int i = 0; i < nlist; i++) {
hist[i] = invlists->list_size(i);
}
return faiss::imbalance_factor(nlist, hist.data());
}
void IndexBinaryIVF::print_stats() const {
std::vector<int> sizes(40);
for (int i = 0; i < nlist; i++) {
for (int j = 0; j < sizes.size(); j++) {
if ((invlists->list_size(i) >> j) == 0) {
sizes[j]++;
break;
}
}
}
for (int i = 0; i < sizes.size(); i++) {
if (sizes[i]) {
printf("list size in < %d: %d instances\n", 1 << i, sizes[i]);
}
}
}
void IndexBinaryIVF::merge_from(IndexBinaryIVF &other, idx_t add_id) {
// minimal sanity checks
FAISS_THROW_IF_NOT(other.d == d);
FAISS_THROW_IF_NOT(other.nlist == nlist);
FAISS_THROW_IF_NOT(other.code_size == code_size);
FAISS_THROW_IF_NOT_MSG((!maintain_direct_map &&
!other.maintain_direct_map),
"direct map copy not implemented");
FAISS_THROW_IF_NOT_MSG(typeid (*this) == typeid (other),
"can only merge indexes of the same type");
invlists->merge_from (other.invlists, add_id);
ntotal += other.ntotal;
other.ntotal = 0;
}
void IndexBinaryIVF::replace_invlists(InvertedLists *il, bool own) {
FAISS_THROW_IF_NOT(il->nlist == nlist &&
il->code_size == code_size);
if (own_invlists) {
delete invlists;
}
invlists = il;
own_invlists = own;
}
void IndexBinaryIVF::train_q1(size_t n, const uint8_t *x, bool verbose) {
if (quantizer->is_trained && (quantizer->ntotal == nlist)) {
if (verbose)
printf("IVF quantizer does not need training.\n");
} else {
if (verbose)
printf("Training level-1 quantizer on %ld vectors in %dD\n", n, d);
Clustering clus(d, nlist, cp);
quantizer->reset();
std::unique_ptr<float[]> x_f(new float[n * d]);
binary_to_real(n * d, x, x_f.get());
IndexFlatL2 index_tmp(d);
if (clustering_index && verbose) {
printf("using clustering_index of dimension %d to do the clustering\n",
clustering_index->d);
}
clus.train(n, x_f.get(), clustering_index ? *clustering_index : index_tmp);
std::unique_ptr<uint8_t[]> x_b(new uint8_t[clus.k * code_size]);
real_to_binary(d * clus.k, clus.centroids.data(), x_b.get());
quantizer->add(clus.k, x_b.get());
quantizer->is_trained = true;
}
}
namespace {
using idx_t = Index::idx_t;
template<class HammingComputer, bool store_pairs>
struct IVFBinaryScannerL2: BinaryInvertedListScanner {
HammingComputer hc;
size_t code_size;
IVFBinaryScannerL2 (size_t code_size): code_size (code_size)
{}
void set_query (const uint8_t *query_vector) override {
hc.set (query_vector, code_size);
}
idx_t list_no;
void set_list (idx_t list_no, uint8_t /* coarse_dis */) override {
this->list_no = list_no;
}
uint32_t distance_to_code (const uint8_t *code) const override {
return hc.hamming (code);
}
size_t scan_codes (size_t n,
const uint8_t *codes,
const idx_t *ids,
int32_t *simi, idx_t *idxi,
size_t k) const override
{
using C = CMax<int32_t, idx_t>;
size_t nup = 0;
for (size_t j = 0; j < n; j++) {
uint32_t dis = hc.hamming (codes);
if (dis < simi[0]) {
heap_pop<C> (k, simi, idxi);
long id = store_pairs ? (list_no << 32 | j) : ids[j];
heap_push<C> (k, simi, idxi, dis, id);
nup++;
}
codes += code_size;
}
return nup;
}
};
template <bool store_pairs>
BinaryInvertedListScanner *select_IVFBinaryScannerL2 (size_t code_size) {
switch (code_size) {
#define HANDLE_CS(cs) \
case cs: \
return new IVFBinaryScannerL2<HammingComputer ## cs, store_pairs> (cs);
HANDLE_CS(4);
HANDLE_CS(8);
HANDLE_CS(16);
HANDLE_CS(20);
HANDLE_CS(32);
HANDLE_CS(64);
#undef HANDLE_CS
default:
if (code_size % 8 == 0) {
return new IVFBinaryScannerL2<HammingComputerM8,
store_pairs> (code_size);
} else if (code_size % 4 == 0) {
return new IVFBinaryScannerL2<HammingComputerM4,
store_pairs> (code_size);
} else {
return new IVFBinaryScannerL2<HammingComputerDefault,
store_pairs> (code_size);
}
}
}
void search_knn_hamming_heap(const IndexBinaryIVF& ivf,
size_t n,
const uint8_t *x,
idx_t k,
const idx_t *keys,
const int32_t * coarse_dis,
int32_t *distances, idx_t *labels,
bool store_pairs,
const IVFSearchParameters *params)
{
long nprobe = params ? params->nprobe : ivf.nprobe;
long max_codes = params ? params->max_codes : ivf.max_codes;
MetricType metric_type = ivf.metric_type;
// almost verbatim copy from IndexIVF::search_preassigned
size_t nlistv = 0, ndis = 0, nheap = 0;
using HeapForIP = CMin<int32_t, idx_t>;
using HeapForL2 = CMax<int32_t, idx_t>;
#pragma omp parallel if(n > 1) reduction(+: nlistv, ndis, nheap)
{
std::unique_ptr<BinaryInvertedListScanner> scanner
(ivf.get_InvertedListScanner (store_pairs));
#pragma omp for
for (size_t i = 0; i < n; i++) {
const uint8_t *xi = x + i * ivf.code_size;
scanner->set_query(xi);
const long * keysi = keys + i * nprobe;
int32_t * simi = distances + k * i;
long * idxi = labels + k * i;
if (metric_type == METRIC_INNER_PRODUCT) {
heap_heapify<HeapForIP> (k, simi, idxi);
} else {
heap_heapify<HeapForL2> (k, simi, idxi);
}
size_t nscan = 0;
for (size_t ik = 0; ik < nprobe; ik++) {
long key = keysi[ik]; /* select the list */
if (key < 0) {
// not enough centroids for multiprobe
continue;
}
FAISS_THROW_IF_NOT_FMT
(key < (long) ivf.nlist,
"Invalid key=%ld at ik=%ld nlist=%ld\n",
key, ik, ivf.nlist);
scanner->set_list (key, coarse_dis[i * nprobe + ik]);
nlistv++;
size_t list_size = ivf.invlists->list_size(key);
InvertedLists::ScopedCodes scodes (ivf.invlists, key);
const Index::idx_t * ids = store_pairs ? nullptr :
ivf.invlists->get_ids (key);
nheap += scanner->scan_codes (list_size, scodes.get(),
ids, simi, idxi, k);
if (ids) {
ivf.invlists->release_ids (ids);
}
nscan += list_size;
if (max_codes && nscan >= max_codes)
break;
}
ndis += nscan;
if (metric_type == METRIC_INNER_PRODUCT) {
heap_reorder<HeapForIP> (k, simi, idxi);
} else {
heap_reorder<HeapForL2> (k, simi, idxi);
}
} // parallel for
} // parallel
indexIVF_stats.nq += n;
indexIVF_stats.nlist += nlistv;
indexIVF_stats.ndis += ndis;
indexIVF_stats.nheap_updates += nheap;
}
template<class HammingComputer, bool store_pairs>
void search_knn_hamming_count(const IndexBinaryIVF& ivf,
size_t nx,
const uint8_t *x,
const long *keys,
int k,
int32_t *distances,
long *labels,
const IVFSearchParameters *params) {
const int nBuckets = ivf.d + 1;
std::vector<int> all_counters(nx * nBuckets, 0);
std::unique_ptr<long[]> all_ids_per_dis(new long[nx * nBuckets * k]);
long nprobe = params ? params->nprobe : ivf.nprobe;
long max_codes = params ? params->max_codes : ivf.max_codes;
std::vector<HCounterState<HammingComputer>> cs;
for (size_t i = 0; i < nx; ++i) {
cs.push_back(HCounterState<HammingComputer>(
all_counters.data() + i * nBuckets,
all_ids_per_dis.get() + i * nBuckets * k,
x + i * ivf.code_size,
ivf.d,
k
));
}
size_t nlistv = 0, ndis = 0;
#pragma omp parallel for reduction(+: nlistv, ndis)
for (size_t i = 0; i < nx; i++) {
const long * keysi = keys + i * nprobe;
HCounterState<HammingComputer>& csi = cs[i];
size_t nscan = 0;
for (size_t ik = 0; ik < nprobe; ik++) {
long key = keysi[ik]; /* select the list */
if (key < 0) {
// not enough centroids for multiprobe
continue;
}
FAISS_THROW_IF_NOT_FMT (
key < (long) ivf.nlist,
"Invalid key=%ld at ik=%ld nlist=%ld\n",
key, ik, ivf.nlist);
nlistv++;
size_t list_size = ivf.invlists->list_size(key);
InvertedLists::ScopedCodes scodes (ivf.invlists, key);
const uint8_t *list_vecs = scodes.get();
const Index::idx_t *ids = store_pairs
? nullptr
: ivf.invlists->get_ids(key);
for (size_t j = 0; j < list_size; j++) {
const uint8_t * yj = list_vecs + ivf.code_size * j;
long id = store_pairs ? (key << 32 | j) : ids[j];
csi.update_counter(yj, id);
}
if (ids)
ivf.invlists->release_ids (ids);
nscan += list_size;
if (max_codes && nscan >= max_codes)
break;
}
ndis += nscan;
int nres = 0;
for (int b = 0; b < nBuckets && nres < k; b++) {
for (int l = 0; l < csi.counters[b] && nres < k; l++) {
labels[i * k + nres] = csi.ids_per_dis[b * k + l];
distances[i * k + nres] = b;
nres++;
}
}
while (nres < k) {
labels[i * k + nres] = -1;
distances[i * k + nres] = std::numeric_limits<int32_t>::max();
++nres;
}
}
indexIVF_stats.nq += nx;
indexIVF_stats.nlist += nlistv;
indexIVF_stats.ndis += ndis;
}
template<bool store_pairs>
void search_knn_hamming_count_1 (
const IndexBinaryIVF& ivf,
size_t nx,
const uint8_t *x,
const long *keys,
int k,
int32_t *distances,
long *labels,
const IVFSearchParameters *params) {
switch (ivf.code_size) {
#define HANDLE_CS(cs) \
case cs: \
search_knn_hamming_count<HammingComputer ## cs, store_pairs>( \
ivf, nx, x, keys, k, distances, labels, params); \
break;
HANDLE_CS(4);
HANDLE_CS(8);
HANDLE_CS(16);
HANDLE_CS(20);
HANDLE_CS(32);
HANDLE_CS(64);
#undef HANDLE_CS
default:
if (ivf.code_size % 8 == 0) {
search_knn_hamming_count<HammingComputerM8, store_pairs>
(ivf, nx, x, keys, k, distances, labels, params);
} else if (ivf.code_size % 4 == 0) {
search_knn_hamming_count<HammingComputerM4, store_pairs>
(ivf, nx, x, keys, k, distances, labels, params);
} else {
search_knn_hamming_count<HammingComputerDefault, store_pairs>
(ivf, nx, x, keys, k, distances, labels, params);
}
break;
}
}
} // namespace
BinaryInvertedListScanner *IndexBinaryIVF::get_InvertedListScanner
(bool store_pairs) const
{
if (store_pairs) {
return select_IVFBinaryScannerL2<true> (code_size);
} else {
return select_IVFBinaryScannerL2<false> (code_size);
}
}
void IndexBinaryIVF::search_preassigned(idx_t n, const uint8_t *x, idx_t k,
const idx_t *idx,
const int32_t * coarse_dis,
int32_t *distances, idx_t *labels,
bool store_pairs,
const IVFSearchParameters *params
) const {
if (use_heap) {
search_knn_hamming_heap (*this, n, x, k, idx, coarse_dis,
distances, labels, store_pairs,
params);
} else {
if (store_pairs) {
search_knn_hamming_count_1<true>
(*this, n, x, idx, k, distances, labels, params);
} else {
search_knn_hamming_count_1<false>
(*this, n, x, idx, k, distances, labels, params);
}
}
}
IndexBinaryIVF::~IndexBinaryIVF() {
if (own_invlists) {
delete invlists;
}
if (own_fields) {
delete quantizer;
}
}
} // namespace faiss
faiss::IndexBinary::search
virtual void search(idx_t n, const uint8_t *x, idx_t k, int32_t *distances, idx_t *labels) const =0
faiss::HammingComputer
Definition: hamming.h:403
faiss::IndexBinaryIVF::nprobe
size_t nprobe
number of probes at query time
Definition: IndexBinaryIVF.h:41
faiss::IndexBinaryIVF::add_core
void add_core(idx_t n, const uint8_t *x, const long *xids, const long *precomputed_idx)
same as add_with_ids, with precomputed coarse quantizer
Definition: IndexBinaryIVF.cpp:65
faiss::ClusteringParameters::niter
int niter
clustering iterations
Definition: Clustering.h:24
faiss::ArrayInvertedLists
simple (default) implementation as an array of inverted lists
Definition: InvertedLists.h:168
faiss::IndexBinaryIVF::reconstruct_from_offset
virtual void reconstruct_from_offset(long list_no, long offset, uint8_t *recons) const
Definition: IndexBinaryIVF.cpp:203
faiss::InvertedLists::get_ids
virtual const idx_t * get_ids(size_t list_no) const =0
faiss::IndexBinary::reset
virtual void reset()=0
Removes all elements from the database.
faiss::IndexBinaryIVF
Definition: IndexBinaryIVF.h:36
faiss::IndexBinaryIVF::maintain_direct_map
bool maintain_direct_map
map for direct access to the elements. Enables reconstruct().
Definition: IndexBinaryIVF.h:50
faiss::IndexBinaryIVF::cp
ClusteringParameters cp
to override default clustering params
Definition: IndexBinaryIVF.h:58
faiss::IndexBinaryIVF::search_preassigned
void search_preassigned(idx_t n, const uint8_t *x, idx_t k, const idx_t *assign, const int32_t *centroid_dis, int32_t *distances, idx_t *labels, bool store_pairs, const IVFSearchParameters *params=nullptr) const
Definition: IndexBinaryIVF.cpp:662
faiss::IndexBinaryIVF::nlist
size_t nlist
number of possible key values
Definition: IndexBinaryIVF.h:54
faiss::IDSelector
Definition: AuxIndexStructures.h:54
faiss::IndexFlatL2
Definition: IndexFlat.h:78
faiss::InvertedLists::list_size
virtual size_t list_size(size_t list_no) const =0
get the size of a list
faiss::IndexBinary::verbose
bool verbose
verbosity level
Definition: IndexBinary.h:43
faiss::Clustering::k
size_t k
nb of centroids
Definition: Clustering.h:59
faiss::imbalance_factor
double imbalance_factor(int n, int k, const long *assign)
a balanced assignment has a IF of 1
Definition: utils.cpp:1292
faiss::IndexBinary::is_trained
bool is_trained
set if the Index does not require training, or if training is done already
Definition: IndexBinary.h:46
faiss::IndexBinaryIVF::quantizer
IndexBinary * quantizer
quantizer that maps vectors to inverted lists
Definition: IndexBinaryIVF.h:53
faiss::IndexBinary::code_size
int code_size
number of bytes per vector ( = d / 8 )
Definition: IndexBinary.h:41
faiss::IVFSearchParameters
Definition: IndexIVF.h:61
faiss::InvertedLists
Definition: InvertedLists.h:32
faiss::IndexBinaryIVF::own_fields
bool own_fields
whether object owns the quantizer
Definition: IndexBinaryIVF.h:56
faiss::IndexBinaryIVF::merge_from
virtual void merge_from(IndexBinaryIVF &other, idx_t add_id)
Definition: IndexBinaryIVF.cpp:286
faiss::IndexBinaryIVF::make_direct_map
void make_direct_map(bool new_maintain_direct_map=true)
Definition: IndexBinaryIVF.cpp:105
faiss::IndexBinary::d
int d
vector dimension
Definition: IndexBinary.h:40
faiss::IndexBinaryIVF::clustering_index
Index * clustering_index
to override index used during clustering
Definition: IndexBinaryIVF.h:59
faiss::InvertedLists::merge_from
void merge_from(InvertedLists *oivf, size_t add_id)
move all entries from oivf (empty on output)
Definition: InvertedLists.cpp:78
faiss::InvertedLists::get_single_id
virtual idx_t get_single_id(size_t list_no, size_t offset) const
Definition: InvertedLists.cpp:36
faiss::Index::d
int d
vector dimension
Definition: Index.h:66
faiss::InvertedLists::code_size
size_t code_size
code size per vector in bytes
Definition: InvertedLists.h:36
faiss::IndexBinaryIVF::train_q1
void train_q1(size_t n, const uint8_t *x, bool verbose)
Trains the quantizer and calls train_residual to train sub-quantizers.
Definition: IndexBinaryIVF.cpp:314
faiss::InvertedLists::get_single_code
virtual const uint8_t * get_single_code(size_t list_no, size_t offset) const
Definition: InvertedLists.cpp:53
faiss::IndexBinaryIVF::imbalance_factor
double imbalance_factor() const
1= perfectly balanced, &gt;1: imbalanced
Definition: IndexBinaryIVF.cpp:259
faiss::IndexBinaryIVF::train
void train(idx_t n, const uint8_t *x) override
Trains the quantizer and calls train_residual to train sub-quantizers.
Definition: IndexBinaryIVF.cpp:250
faiss::Clustering
Definition: Clustering.h:56
faiss::IndexBinaryIVF::use_heap
bool use_heap
Definition: IndexBinaryIVF.h:47
faiss::IndexBinary::assign
void assign(idx_t n, const uint8_t *x, idx_t *labels, idx_t k=1)
Definition: IndexBinary.cpp:29
faiss::InvertedLists::add_entry
virtual size_t add_entry(size_t list_no, idx_t theid, const uint8_t *code)
add one entry to an inverted list
Definition: InvertedLists.cpp:60
faiss::IndexBinaryIVF::reset
void reset() override
Removes all elements from the database.
Definition: IndexBinaryIVF.cpp:208
faiss::Index::idx_t
long idx_t
all indices are this type
Definition: Index.h:64
faiss::Clustering::centroids
std::vector< float > centroids
centroids (k * d)
Definition: Clustering.h:62
faiss::InvertedLists::prefetch_lists
virtual void prefetch_lists(const long *list_nos, int nlist) const
Definition: InvertedLists.cpp:50
faiss::real_to_binary
void real_to_binary(size_t d, const float *x_in, uint8_t *x_out)
Definition: utils.cpp:1558
faiss::IndexBinaryIVF::print_stats
void print_stats() const
display some stats about the inverted lists
Definition: IndexBinaryIVF.cpp:269
faiss::IndexBinaryIVF::add_with_ids
void add_with_ids(idx_t n, const uint8_t *x, const long *xids) override
Definition: IndexBinaryIVF.cpp:61
faiss::IndexBinaryIVF::add
void add(idx_t n, const uint8_t *x) override
Quantizes x and calls add_with_key.
Definition: IndexBinaryIVF.cpp:57
faiss::InvertedLists::nlist
size_t nlist
number of possible key values
Definition: InvertedLists.h:35
faiss::IndexBinaryIVF::remove_ids
long remove_ids(const IDSelector &sel) override
Dataset manipulation functions.
Definition: IndexBinaryIVF.cpp:214
faiss::IndexBinary::ntotal
idx_t ntotal
total nb of indexed vectors
Definition: IndexBinary.h:42
faiss::BinaryInvertedListScanner
Definition: IndexBinaryIVF.h:187
faiss::IndexBinary
Definition: IndexBinary.h:37
faiss::IndexBinary::idx_t
long idx_t
all indices are this type
Definition: IndexBinary.h:38
faiss::IndexBinary::add
virtual void add(idx_t n, const uint8_t *x)=0
faiss::IndexBinaryIVF::search
virtual void search(idx_t n, const uint8_t *x, idx_t k, int32_t *distances, idx_t *labels) const override
Definition: IndexBinaryIVF.cpp:128
faiss::Clustering::train
virtual void train(idx_t n, const float *x, faiss::Index &index)
Index is used during the assignment stage.
Definition: Clustering.cpp:64
faiss::binary_to_real
void binary_to_real(size_t d, const uint8_t *x_in, float *x_out)
Definition: utils.cpp:1552
faiss::IndexBinaryIVF::search_and_reconstruct
void search_and_reconstruct(idx_t n, const uint8_t *x, idx_t k, int32_t *distances, idx_t *labels, uint8_t *recons) const override
Definition: IndexBinaryIVF.cpp:168
faiss::IndexBinaryIVF::reconstruct_n
void reconstruct_n(idx_t i0, idx_t ni, uint8_t *recons) const override
Definition: IndexBinaryIVF.cpp:149
faiss::IndexBinaryIVF::reconstruct
void reconstruct(idx_t key, uint8_t *recons) const override
Definition: IndexBinaryIVF.cpp:141
faiss::MetricType
MetricType
Some algorithms support both an inner product version and a L2 search version.
Definition: Index.h:45
faiss::IndexBinaryIVF::invlists
InvertedLists * invlists
Acess to the actual data.
Definition: IndexBinaryIVF.h:38