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GpuIndexIVFPQ.cu
/**
* 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.
#include "GpuIndexIVFPQ.h"
#include "../IndexFlat.h"
#include "../IndexIVFPQ.h"
#include "../ProductQuantizer.h"
#include "GpuIndexFlat.h"
#include "GpuResources.h"
#include "impl/IVFPQ.cuh"
#include "utils/CopyUtils.cuh"
#include "utils/DeviceUtils.h"
#include <limits>
namespace faiss { namespace gpu {
GpuIndexIVFPQ::GpuIndexIVFPQ(GpuResources* resources,
const faiss::IndexIVFPQ* index,
GpuIndexIVFPQConfig config) :
GpuIndexIVF(resources,
index->d,
index->metric_type,
index->nlist,
config),
ivfpqConfig_(config),
subQuantizers_(0),
bitsPerCode_(0),
reserveMemoryVecs_(0),
index_(nullptr) {
#ifndef FAISS_USE_FLOAT16
FAISS_ASSERT(!ivfpqConfig_.useFloat16LookupTables);
#endif
copyFrom(index);
}
GpuIndexIVFPQ::GpuIndexIVFPQ(GpuResources* resources,
int dims,
int nlist,
int subQuantizers,
int bitsPerCode,
faiss::MetricType metric,
GpuIndexIVFPQConfig config) :
GpuIndexIVF(resources,
dims,
metric,
nlist,
config),
ivfpqConfig_(config),
subQuantizers_(subQuantizers),
bitsPerCode_(bitsPerCode),
reserveMemoryVecs_(0),
index_(nullptr) {
#ifndef FAISS_USE_FLOAT16
FAISS_ASSERT(!useFloat16LookupTables_);
#endif
verifySettings_();
// FIXME make IP work fully
FAISS_ASSERT(this->metric_type == faiss::METRIC_L2);
// We haven't trained ourselves, so don't construct the PQ index yet
this->is_trained = false;
}
GpuIndexIVFPQ::~GpuIndexIVFPQ() {
delete index_;
}
void
GpuIndexIVFPQ::copyFrom(const faiss::IndexIVFPQ* index) {
DeviceScope scope(device_);
// FIXME: support this
FAISS_THROW_IF_NOT_MSG(index->metric_type == faiss::METRIC_L2,
"inner product unsupported");
GpuIndexIVF::copyFrom(index);
// Clear out our old data
delete index_;
index_ = nullptr;
subQuantizers_ = index->pq.M;
bitsPerCode_ = index->pq.nbits;
// We only support this
FAISS_ASSERT(index->pq.byte_per_idx == 1);
FAISS_ASSERT(index->by_residual);
FAISS_ASSERT(index->polysemous_ht == 0);
ivfpqConfig_.usePrecomputedTables = (bool) index->use_precomputed_table;
verifySettings_();
// The other index might not be trained
if (!index->is_trained) {
return;
}
// Otherwise, we can populate ourselves from the other index
this->is_trained = true;
// Copy our lists as well
// The product quantizer must have data in it
FAISS_ASSERT(index->pq.centroids.size() > 0);
index_ = new IVFPQ(resources_,
quantizer_->getGpuData(),
subQuantizers_,
bitsPerCode_,
(float*) index->pq.centroids.data(),
ivfpqConfig_.indicesOptions,
ivfpqConfig_.useFloat16LookupTables,
memorySpace_);
// Doesn't make sense to reserve memory here
index_->setPrecomputedCodes(ivfpqConfig_.usePrecomputedTables);
// Copy database vectors, if any
for (size_t i = 0; i < index->codes.size(); ++i) {
auto& codes = index->codes[i];
auto& ids = index->ids[i];
FAISS_ASSERT(ids.size() * subQuantizers_ == codes.size());
// GPU index can only support max int entries per list
FAISS_THROW_IF_NOT_FMT(ids.size() <=
(size_t) std::numeric_limits<int>::max(),
"GPU inverted list can only support "
"%zu entries; %zu found",
(size_t) std::numeric_limits<int>::max(),
ids.size());
index_->addCodeVectorsFromCpu(i, codes.data(), ids.data(), ids.size());
}
}
void
GpuIndexIVFPQ::copyTo(faiss::IndexIVFPQ* index) const {
DeviceScope scope(device_);
// We must have the indices in order to copy to ourselves
FAISS_THROW_IF_NOT_MSG(ivfpqConfig_.indicesOptions != INDICES_IVF,
"Cannot copy to CPU as GPU index doesn't retain "
"indices (INDICES_IVF)");
GpuIndexIVF::copyTo(index);
//
// IndexIVFPQ information
//
index->by_residual = true;
index->use_precomputed_table = 0;
index->code_size = subQuantizers_;
index->pq = faiss::ProductQuantizer(this->d, subQuantizers_, bitsPerCode_);
index->do_polysemous_training = false;
index->polysemous_training = nullptr;
index->scan_table_threshold = 0;
index->max_codes = 0;
index->polysemous_ht = 0;
index->codes.clear();
index->codes.resize(nlist_);
index->precomputed_table.clear();
if (index_) {
// Copy the inverted lists
for (int i = 0; i < nlist_; ++i) {
index->ids[i] = getListIndices(i);
index->codes[i] = getListCodes(i);
}
// Copy PQ centroids
auto devPQCentroids = index_->getPQCentroids();
index->pq.centroids.resize(devPQCentroids.numElements());
fromDevice<float, 3>(devPQCentroids,
index->pq.centroids.data(),
resources_->getDefaultStream(device_));
if (ivfpqConfig_.usePrecomputedTables) {
index->precompute_table();
}
}
}
void
GpuIndexIVFPQ::reserveMemory(size_t numVecs) {
reserveMemoryVecs_ = numVecs;
if (index_) {
DeviceScope scope(device_);
index_->reserveMemory(numVecs);
}
}
void
GpuIndexIVFPQ::setPrecomputedCodes(bool enable) {
ivfpqConfig_.usePrecomputedTables = enable;
if (index_) {
DeviceScope scope(device_);
index_->setPrecomputedCodes(enable);
}
verifySettings_();
}
bool
GpuIndexIVFPQ::getPrecomputedCodes() const {
return ivfpqConfig_.usePrecomputedTables;
}
int
GpuIndexIVFPQ::getNumSubQuantizers() const {
return subQuantizers_;
}
int
GpuIndexIVFPQ::getBitsPerCode() const {
return bitsPerCode_;
}
int
GpuIndexIVFPQ::getCentroidsPerSubQuantizer() const {
return utils::pow2(bitsPerCode_);
}
size_t
GpuIndexIVFPQ::reclaimMemory() {
if (index_) {
DeviceScope scope(device_);
return index_->reclaimMemory();
}
return 0;
}
void
GpuIndexIVFPQ::reset() {
if (index_) {
DeviceScope scope(device_);
index_->reset();
this->ntotal = 0;
} else {
FAISS_ASSERT(this->ntotal == 0);
}
}
void
GpuIndexIVFPQ::trainResidualQuantizer_(Index::idx_t n, const float* x) {
// Code largely copied from faiss::IndexIVFPQ
// FIXME: GPUize more of this
n = std::min(n, (Index::idx_t) (1 << bitsPerCode_) * 64);
if (this->verbose) {
printf("computing residuals\n");
}
std::vector<Index::idx_t> assign(n);
quantizer_->assign (n, x, assign.data());
std::vector<float> residuals(n * d);
for (idx_t i = 0; i < n; i++) {
quantizer_->compute_residual(x + i * d, &residuals[i * d], assign[i]);
}
if (this->verbose) {
printf("training %d x %d product quantizer on %ld vectors in %dD\n",
subQuantizers_, getCentroidsPerSubQuantizer(), n, this->d);
}
// Just use the CPU product quantizer to determine sub-centroids
faiss::ProductQuantizer pq(this->d, subQuantizers_, bitsPerCode_);
pq.verbose = this->verbose;
pq.train(n, residuals.data());
index_ = new IVFPQ(resources_,
quantizer_->getGpuData(),
subQuantizers_,
bitsPerCode_,
pq.centroids.data(),
ivfpqConfig_.indicesOptions,
ivfpqConfig_.useFloat16LookupTables,
memorySpace_);
if (reserveMemoryVecs_) {
index_->reserveMemory(reserveMemoryVecs_);
}
index_->setPrecomputedCodes(ivfpqConfig_.usePrecomputedTables);
}
void
GpuIndexIVFPQ::train(Index::idx_t n, const float* x) {
DeviceScope scope(device_);
if (this->is_trained) {
FAISS_ASSERT(quantizer_->is_trained);
FAISS_ASSERT(quantizer_->ntotal == nlist_);
FAISS_ASSERT(index_);
return;
}
FAISS_ASSERT(!index_);
trainQuantizer_(n, x);
trainResidualQuantizer_(n, x);
this->is_trained = true;
}
void
GpuIndexIVFPQ::addImpl_(Index::idx_t n,
const float* x,
const Index::idx_t* xids) {
// Device is already set in GpuIndex::addInternal_
FAISS_ASSERT(index_);
FAISS_ASSERT(n > 0);
auto stream = resources_->getDefaultStreamCurrentDevice();
auto deviceVecs =
toDevice<float, 2>(resources_,
device_,
const_cast<float*>(x),
stream,
{(int) n, index_->getDim()});
auto deviceIndices =
toDevice<Index::idx_t, 1>(resources_,
device_,
const_cast< Index::idx_t*>(xids),
stream,
{(int) n});
// Not all vectors may be able to be added (some may contain NaNs
// etc)
ntotal += index_->classifyAndAddVectors(deviceVecs, deviceIndices);
}
void
GpuIndexIVFPQ::searchImpl_(faiss::Index::idx_t n,
const float* x,
faiss::Index::idx_t k,
float* distances,
faiss::Index::idx_t* labels) const {
// Device is already set in GpuIndex::search
FAISS_ASSERT(index_);
FAISS_ASSERT(n > 0);
// Make sure arguments are on the device we desire; use temporary
// memory allocations to move it if necessary
auto devX =
toDevice<float, 2>(resources_,
device_,
const_cast<float*>(x),
resources_->getDefaultStream(device_),
{(int) n, index_->getDim()});
auto devDistances =
toDevice<float, 2>(resources_,
device_,
distances,
resources_->getDefaultStream(device_),
{(int) n, (int) k});
auto devLabels =
toDevice<faiss::Index::idx_t, 2>(resources_,
device_,
labels,
resources_->getDefaultStream(device_),
{(int) n, (int) k});
index_->query(devX,
nprobe_,
(int) k,
devDistances,
devLabels);
// Copy back if necessary
fromDevice<float, 2>(
devDistances, distances, resources_->getDefaultStream(device_));
fromDevice<faiss::Index::idx_t, 2>(
devLabels, labels, resources_->getDefaultStream(device_));
}
int
GpuIndexIVFPQ::getListLength(int listId) const {
FAISS_ASSERT(index_);
return index_->getListLength(listId);
}
std::vector<unsigned char>
GpuIndexIVFPQ::getListCodes(int listId) const {
FAISS_ASSERT(index_);
DeviceScope scope(device_);
return index_->getListCodes(listId);
}
std::vector<long>
GpuIndexIVFPQ::getListIndices(int listId) const {
FAISS_ASSERT(index_);
DeviceScope scope(device_);
return index_->getListIndices(listId);
}
void
GpuIndexIVFPQ::verifySettings_() const {
// Our implementation has these restrictions:
// Must have some number of lists
FAISS_THROW_IF_NOT_MSG(nlist_ > 0, "nlist must be >0");
// up to a single byte per code
FAISS_THROW_IF_NOT_FMT(bitsPerCode_ <= 8,
"Bits per code must be <= 8 (passed %d)", bitsPerCode_);
// Sub-quantizers must evenly divide dimensions available
FAISS_THROW_IF_NOT_FMT(this->d % subQuantizers_ == 0,
"Number of sub-quantizers (%d) must be an "
"even divisor of the number of dimensions (%d)",
subQuantizers_, this->d);
// The number of bytes per encoded vector must be one we support
FAISS_THROW_IF_NOT_FMT(IVFPQ::isSupportedPQCodeLength(subQuantizers_),
"Number of bytes per encoded vector / sub-quantizers (%d) "
"is not supported",
subQuantizers_);
// We must have enough shared memory on the current device to store
// our lookup distances
int lookupTableSize = sizeof(float);
#ifdef FAISS_USE_FLOAT16
if (ivfpqConfig_.useFloat16LookupTables) {
lookupTableSize = sizeof(half);
}
#endif
// 64 bytes per code is only supported with usage of float16, at 2^8
// codes per subquantizer
size_t requiredSmemSize =
lookupTableSize * subQuantizers_ * utils::pow2(bitsPerCode_);
size_t smemPerBlock = getMaxSharedMemPerBlock(device_);
FAISS_THROW_IF_NOT_FMT(requiredSmemSize
<= getMaxSharedMemPerBlock(device_),
"Device %d has %zu bytes of shared memory, while "
"%d bits per code and %d sub-quantizers requires %zu "
"bytes. Consider useFloat16LookupTables and/or "
"reduce parameters",
device_, smemPerBlock, bitsPerCode_, subQuantizers_,
requiredSmemSize);
// If precomputed codes are disabled, we have an extra limitation in
// terms of the number of dimensions per subquantizer
FAISS_THROW_IF_NOT_FMT(ivfpqConfig_.usePrecomputedTables ||
IVFPQ::isSupportedNoPrecomputedSubDimSize(
this->d / subQuantizers_),
"Number of dimensions per sub-quantizer (%d) "
"is unsupported with precomputed codes",
this->d / subQuantizers_);
// TODO: fully implement METRIC_INNER_PRODUCT
FAISS_THROW_IF_NOT_MSG(this->metric_type == faiss::METRIC_L2,
"METRIC_INNER_PRODUCT is currently unsupported");
}
} } // namespace
faiss::gpu::GpuIndexIVFPQ::getListIndices
std::vector< long > getListIndices(int listId) const
Definition: GpuIndexIVFPQ.cu:408
faiss::gpu::GpuIndexIVFPQ::searchImpl_
void searchImpl_(faiss::Index::idx_t n, const float *x, faiss::Index::idx_t k, float *distances, faiss::Index::idx_t *labels) const override
Called from GpuIndex for search.
Definition: GpuIndexIVFPQ.cu:349
faiss::IndexIVFPQ::precompute_table
void precompute_table()
build precomputed table
Definition: IndexIVFPQ.cpp:391
faiss::gpu::GpuIndexIVFPQ::reset
void reset() override
Definition: GpuIndexIVFPQ.cu:245
faiss::ProductQuantizer::nbits
size_t nbits
number of bits per quantization index
Definition: ProductQuantizer.h:29
faiss::gpu::GpuResources::getDefaultStreamCurrentDevice
cudaStream_t getDefaultStreamCurrentDevice()
Calls getDefaultStream with the current device.
Definition: GpuResources.cpp:25
faiss::gpu::GpuIndexIVFPQConfig::usePrecomputedTables
bool usePrecomputedTables
Definition: GpuIndexIVFPQ.h:36
faiss::IndexIVFPQ::polysemous_training
PolysemousTraining * polysemous_training
if NULL, use default
Definition: IndexIVFPQ.h:36
faiss::ProductQuantizer::byte_per_idx
size_t byte_per_idx
nb bytes per code component (1 or 2)
Definition: ProductQuantizer.h:33
faiss::gpu::GpuIndexIVFPQ::GpuIndexIVFPQ
GpuIndexIVFPQ(GpuResources *resources, const faiss::IndexIVFPQ *index, GpuIndexIVFPQConfig config=GpuIndexIVFPQConfig())
Definition: GpuIndexIVFPQ.cu:25
faiss::gpu::IVFBase::getDim
int getDim() const
Return the number of dimensions we are indexing.
Definition: IVFBase.cu:100
faiss::gpu::IVFBase::getListLength
int getListLength(int listId) const
Definition: IVFBase.cu:200
faiss::gpu::GpuIndexFlat::getGpuData
FlatIndex * getGpuData()
For internal access.
Definition: GpuIndexFlat.h:120
faiss::Index::assign
void assign(idx_t n, const float *x, idx_t *labels, idx_t k=1)
Definition: Index.cpp:23
faiss::gpu::IVFBase::reserveMemory
void reserveMemory(size_t numVecs)
Reserve GPU memory in our inverted lists for this number of vectors.
Definition: IVFBase.cu:45
faiss::gpu::GpuIndexIVFPQ::getListLength
int getListLength(int listId) const
Definition: GpuIndexIVFPQ.cu:394
faiss::IndexIVFPQ::do_polysemous_training
bool do_polysemous_training
reorder PQ centroids after training?
Definition: IndexIVFPQ.h:35
faiss::IndexIVFPQ::scan_table_threshold
size_t scan_table_threshold
use table computation or on-the-fly?
Definition: IndexIVFPQ.h:39
faiss::IndexIVFPQ::precomputed_table
std::vector< float > precomputed_table
Definition: IndexIVFPQ.h:47
faiss::IndexIVFPQ::polysemous_ht
int polysemous_ht
Hamming thresh for polysemous filtering.
Definition: IndexIVFPQ.h:41
faiss::gpu::GpuResources
Definition: GpuResources.h:23
faiss::gpu::GpuIndexIVFPQ::getBitsPerCode
int getBitsPerCode() const
Return the number of bits per PQ code.
Definition: GpuIndexIVFPQ.cu:225
faiss::gpu::GpuIndexIVFPQConfig::useFloat16LookupTables
bool useFloat16LookupTables
Definition: GpuIndexIVFPQ.h:32
faiss::gpu::GpuResources::getDefaultStream
virtual cudaStream_t getDefaultStream(int device)=0
faiss::IndexIVF::ids
std::vector< std::vector< long > > ids
Inverted lists for indexes.
Definition: IndexIVF.h:55
faiss::gpu::GpuIndexIVF
Definition: GpuIndexIVF.h:37
faiss::Index::d
int d
vector dimension
Definition: Index.h:64
faiss::gpu::GpuIndexIVFPQ::train
void train(Index::idx_t n, const float *x) override
Definition: GpuIndexIVFPQ.cu:301
faiss::IndexIVFPQ::max_codes
size_t max_codes
max nb of codes to visit to do a query
Definition: IndexIVFPQ.h:40
faiss::gpu::IVFPQ::isSupportedPQCodeLength
static bool isSupportedPQCodeLength(int size)
Returns true if we support PQ in this size.
Definition: IVFPQ.cu:72
faiss::gpu::GpuIndexIVFPQ::reclaimMemory
size_t reclaimMemory()
Definition: GpuIndexIVFPQ.cu:235
faiss::gpu::GpuIndexIVFPQConfig
Definition: GpuIndexIVFPQ.h:23
faiss::IndexIVFPQ
Definition: IndexIVFPQ.h:29
faiss::gpu::GpuIndexIVF::nprobe_
int nprobe_
Number of inverted list probes per query.
Definition: GpuIndexIVF.h:86
faiss::gpu::GpuIndexIVFPQ::reserveMemory
void reserveMemory(size_t numVecs)
Reserve GPU memory in our inverted lists for this number of vectors.
Definition: GpuIndexIVFPQ.cu:195
faiss::gpu::IVFPQ::classifyAndAddVectors
int classifyAndAddVectors(Tensor< float, 2, true > &vecs, Tensor< long, 1, true > &indices)
Definition: IVFPQ.cu:120
faiss::gpu::IVFPQ::query
void query(Tensor< float, 2, true > &queries, int nprobe, int k, Tensor< float, 2, true > &outDistances, Tensor< long, 2, true > &outIndices)
Definition: IVFPQ.cu:519
faiss::gpu::GpuIndex::device_
const int device_
The GPU device we are resident on.
Definition: GpuIndex.h:94
faiss::gpu::GpuIndexIVFPQ::copyFrom
void copyFrom(const faiss::IndexIVFPQ *index)
Definition: GpuIndexIVFPQ.cu:80
faiss::gpu::IVFPQ::getPQCentroids
Tensor< float, 3, true > getPQCentroids()
Definition: IVFPQ.cu:594
faiss::gpu::GpuIndex::resources_
GpuResources * resources_
Manages streans, cuBLAS handles and scratch memory for devices.
Definition: GpuIndex.h:91
faiss::gpu::GpuIndexIVF::copyTo
void copyTo(faiss::IndexIVF *index) const
Copy what we have to the CPU equivalent.
Definition: GpuIndexIVF.cu:148
faiss::Index::idx_t
long idx_t
all indices are this type
Definition: Index.h:62
faiss::gpu::GpuIndexIVF::nlist_
int nlist_
Number of inverted lists that we manage.
Definition: GpuIndexIVF.h:83
faiss::gpu::GpuIndexIVFPQ::addImpl_
void addImpl_(faiss::Index::idx_t n, const float *x, const faiss::Index::idx_t *ids) override
Called from GpuIndex for add/add_with_ids.
Definition: GpuIndexIVFPQ.cu:320
faiss::Index::ntotal
idx_t ntotal
total nb of indexed vectors
Definition: Index.h:65
faiss::Index::verbose
bool verbose
verbosity level
Definition: Index.h:66
faiss::gpu::IVFPQ::setPrecomputedCodes
void setPrecomputedCodes(bool enable)
Enable or disable pre-computed codes.
Definition: IVFPQ.cu:102
faiss::gpu::IVFPQ::getListCodes
std::vector< unsigned char > getListCodes(int listId) const
Return the list codes of a particular list back to the CPU.
Definition: IVFPQ.cu:586
faiss::gpu::GpuIndexIVFPQ::copyTo
void copyTo(faiss::IndexIVFPQ *index) const
Definition: GpuIndexIVFPQ.cu:145
faiss::gpu::IVFBase::reset
void reset()
Definition: IVFBase.cu:75
faiss::gpu::DeviceScope
Definition: DeviceUtils.h:62
faiss::gpu::GpuIndex::memorySpace_
const MemorySpace memorySpace_
The memory space of our primary storage on the GPU.
Definition: GpuIndex.h:97
faiss::IndexIVFPQ::by_residual
bool by_residual
Encode residual or plain vector?
Definition: IndexIVFPQ.h:30
faiss::gpu::GpuIndexIVF::quantizer_
GpuIndexFlat * quantizer_
Quantizer for inverted lists.
Definition: GpuIndexIVF.h:92
faiss::Index::metric_type
MetricType metric_type
type of metric this index uses for search
Definition: Index.h:72
faiss::IndexIVFPQ::pq
ProductQuantizer pq
produces the codes
Definition: IndexIVFPQ.h:33
faiss::ProductQuantizer::M
size_t M
number of subquantizers
Definition: ProductQuantizer.h:28
faiss::gpu::GpuIndexIVFPQ::getNumSubQuantizers
int getNumSubQuantizers() const
Return the number of sub-quantizers we are using.
Definition: GpuIndexIVFPQ.cu:220
faiss::gpu::IVFBase::getListIndices
std::vector< long > getListIndices(int listId) const
Return the list indices of a particular list back to the CPU.
Definition: IVFBase.cu:207
faiss::gpu::GpuIndexIVFPQ::getCentroidsPerSubQuantizer
int getCentroidsPerSubQuantizer() const
Return the number of centroids per PQ code (2^bits per code)
Definition: GpuIndexIVFPQ.cu:230
faiss::IndexIVFPQ::code_size
size_t code_size
code size per vector in bytes
Definition: IndexIVFPQ.h:32
faiss::gpu::GpuIndexIVFPQ::setPrecomputedCodes
void setPrecomputedCodes(bool enable)
Enable or disable pre-computed codes.
Definition: GpuIndexIVFPQ.cu:204
faiss::ProductQuantizer
Definition: ProductQuantizer.h:25
faiss::gpu::GpuIndexIVF::copyFrom
void copyFrom(const faiss::IndexIVF *index)
Copy what we need from the CPU equivalent.
Definition: GpuIndexIVF.cu:80
faiss::Index::is_trained
bool is_trained
set if the Index does not require training, or if training is done already
Definition: Index.h:69
faiss::Index::compute_residual
void compute_residual(const float *x, float *residual, idx_t key) const
Definition: Index.cpp:57
faiss::gpu::GpuIndexIVFPQ::getPrecomputedCodes
bool getPrecomputedCodes() const
Are pre-computed codes enabled?
Definition: GpuIndexIVFPQ.cu:215
faiss::gpu::GpuIndexIVFConfig::indicesOptions
IndicesOptions indicesOptions
Index storage options for the GPU.
Definition: GpuIndexIVF.h:31
faiss::gpu::IVFBase::reclaimMemory
size_t reclaimMemory()
Definition: IVFBase.cu:105
faiss::gpu::IVFPQ
Implementing class for IVFPQ on the GPU.
Definition: IVFPQ.cuh:19
faiss::MetricType
MetricType
Some algorithms support both an inner product vetsion and a L2 search version.
Definition: Index.h:43
faiss::IndexIVFPQ::use_precomputed_table
int use_precomputed_table
if by_residual, build precompute tables
Definition: IndexIVFPQ.h:31
faiss::gpu::GpuIndexIVFPQ::getListCodes
std::vector< unsigned char > getListCodes(int listId) const
Definition: GpuIndexIVFPQ.cu:400
faiss::ProductQuantizer::centroids
std::vector< float > centroids
Centroid table, size M * ksub * dsub.
Definition: ProductQuantizer.h:52
faiss::gpu::IVFPQ::isSupportedNoPrecomputedSubDimSize
static bool isSupportedNoPrecomputedSubDimSize(int dims)
Definition: IVFPQ.cu:97