File IndexScalarQuantizer.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.

struct IndexIVFScalarQuantizer : public faiss::IndexIVF
#include <IndexScalarQuantizer.h>

An IVF implementation where the components of the residuals are encoded with a scalar quantizer. All distance computations are asymmetric, so the encoded vectors are decoded and approximate distances are computed.

Public Functions

IndexIVFScalarQuantizer(Index *quantizer, size_t d, size_t nlist, ScalarQuantizer::QuantizerType qtype, MetricType metric = METRIC_L2, bool encode_residual = true)
IndexIVFScalarQuantizer()
virtual void train_residual(idx_t n, const float *x) override

Sub-classes that encode the residuals can train their encoders here does nothing by default

virtual void encode_vectors(idx_t n, const float *x, const idx_t *list_nos, uint8_t *codes, bool include_listnos = false) const override

Encodes a set of vectors as they would appear in the inverted lists

Parameters

  • list_nos – inverted list ids as returned by the quantizer (size n). -1s are ignored.

  • codes – output codes, size n * code_size

  • include_listno – include the list ids in the code (in this case add ceil(log8(nlist)) to the code size)

virtual void add_core(idx_t n, const float *x, const idx_t *xids, const idx_t *precomputed_idx) override

Implementation of vector addition where the vector assignments are predefined. The default implementation hands over the code extraction to encode_vectors.

Parameters

precomputed_idx – quantization indices for the input vectors (size n)

virtual InvertedListScanner *get_InvertedListScanner(bool store_pairs) const override

Get a scanner for this index (store_pairs means ignore labels)

The default search implementation uses this to compute the distances

virtual void reconstruct_from_offset(int64_t list_no, int64_t offset, float *recons) const override

Reconstruct a vector given the location in terms of (inv list index + inv list offset) instead of the id.

Useful for reconstructing when the direct_map is not maintained and the inv list offset is computed by search_preassigned() with store_pairs set.

virtual void sa_decode(idx_t n, const uint8_t *bytes, float *x) const override

decode a set of vectors

Parameters

  • n – number of vectors

  • bytes – input encoded vectors, size n * sa_code_size()

  • x – output vectors, size n * d

Public Members

ScalarQuantizer sq
bool by_residual
struct IndexScalarQuantizer : public faiss::IndexFlatCodes
#include <IndexScalarQuantizer.h>

Flat index built on a scalar quantizer.

Public Functions

IndexScalarQuantizer(int d, ScalarQuantizer::QuantizerType qtype, MetricType metric = METRIC_L2)

Constructor.

Parameters

  • d – dimensionality of the input vectors

  • M – number of subquantizers

  • nbits – number of bit per subvector index

IndexScalarQuantizer()
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 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

virtual FlatCodesDistanceComputer *get_FlatCodesDistanceComputer() const override

a FlatCodesDistanceComputer offers a distance_to_code method

virtual void sa_encode(idx_t n, const float *x, uint8_t *bytes) const override

encode a set of vectors

Parameters

  • n – number of vectors

  • x – input vectors, size n * d

  • bytes – output encoded vectors, size n * sa_code_size()

virtual void sa_decode(idx_t n, const uint8_t *bytes, float *x) const override

decode a set of vectors

Parameters

  • n – number of vectors

  • bytes – input encoded vectors, size n * sa_code_size()

  • x – output vectors, size n * d

Public Members

ScalarQuantizer sq

Used to encode the vectors.