File IndexPQFastScan.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.

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 FastScanStats FastScan_stats
struct FastScanStats

Public Functions

inline FastScanStats()
inline void reset()

Public Members

uint64_t t0
uint64_t t1
uint64_t t2
uint64_t t3
struct IndexPQFastScan : public faiss::Index
#include <IndexPQFastScan.h>

Fast scan version of IndexPQ. Works for 4-bit PQ for now.

The codes are not stored sequentially but grouped in blocks of size bbs. This makes it possible to compute distances quickly with SIMD instructions.

Implementations: 12: blocked loop with internal loop on Q with qbs 13: same with reservoir accumulator to store results 14: no qbs with heap accumulator 15: no qbs with reservoir accumulator

Public Functions

IndexPQFastScan(int d, size_t M, size_t nbits, MetricType metric = METRIC_L2, int bbs = 32)
IndexPQFastScan()
explicit IndexPQFastScan(const IndexPQ &orig, int bbs = 32)

build from an existing IndexPQ

virtual void train(idx_t n, const float *x) override

Perform training on a representative set of vectors

Parameters
  • n – nb of training vectors

  • x – training vecors, size n * d

virtual void add(idx_t n, const float *x) override

Add n vectors of dimension d to the index.

Vectors are implicitly assigned labels ntotal .. ntotal + n - 1 This function slices the input vectors in chunks smaller than blocksize_add and calls add_core.

Parameters

x – input matrix, size n * d

virtual void reset() override

removes all elements from the database.

virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override

query n vectors of dimension d to the index.

return at most k vectors. If there are not enough results for a query, the result array is padded with -1s.

Parameters
  • x – input vectors to search, size n * d

  • labels – output labels of the NNs, size n*k

  • distances – output pairwise distances, size n*k

void compute_quantized_LUT(idx_t n, const float *x, uint8_t *lut, float *normalizers) const
template<bool is_max>
void search_dispatch_implem(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const
template<class C>
void search_implem_2(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const
template<class C>
void search_implem_12(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels, int impl) const
template<class C>
void search_implem_14(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels, int impl) const

Public Members

ProductQuantizer pq
int implem = 0
int skip = 0
int bbs
int qbs = 0
size_t ntotal2
size_t M2
AlignedTable<uint8_t> codes
const uint8_t *orig_codes = nullptr