File IndexPreTransform.h

namespace faiss

Implementation of k-means clustering with many variants.

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.

IDSelector is intended to define a subset of vectors to handle (for removal or as subset to search)

PQ4 SIMD packing and accumulation functions

The basic kernel accumulates nq query vectors with bbs = nb * 2 * 16 vectors and produces an output matrix for that. It is interesting for nq * nb <= 4, otherwise register spilling becomes too large.

The implementation of these functions is spread over 3 cpp files to reduce parallel compile times. Templates are instantiated explicitly.

This file contains callbacks for kernels that compute distances.

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.

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.

Definition of inverted lists + a few common classes that implement the interface.

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.

In this file are the implementations of extra metrics beyond L2 and inner product

Implements a few neural net layers, mainly to support QINCo

Defines a few objects that apply transformations to a set of vectors Often these are pre-processing steps.

struct SearchParametersPreTransform : public faiss::SearchParameters

Public Members

SearchParameters *index_params = nullptr
struct IndexPreTransform : public faiss::Index
#include <IndexPreTransform.h>

Index that applies a LinearTransform transform on vectors before handing them over to a sub-index

Public Functions

explicit IndexPreTransform(Index *index)

! whether pointers are deleted in destructor

IndexPreTransform()
IndexPreTransform(VectorTransform *ltrans, Index *index)

ltrans is the last transform before the index

void prepend_transform(VectorTransform *ltrans)
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:

  • n – number of vectors

  • x – input matrix, size n * d

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

Same as add, but stores xids instead of sequential ids.

The default implementation fails with an assertion, as it is not supported by all indexes.

Parameters:

  • n – number of vectors

  • x – input vectors, size n * d

  • xids – if non-null, ids to store for the vectors (size n)

virtual void reset() override

removes all elements from the database.

virtual size_t remove_ids(const IDSelector &sel) override

removes IDs from the index. Not supported by all indexes.

virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels, const SearchParameters *params = nullptr) 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:

  • n – number of vectors

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

  • k – number of extracted vectors

  • distances – output pairwise distances, size n*k

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

virtual void range_search(idx_t n, const float *x, float radius, RangeSearchResult *result, const SearchParameters *params = nullptr) const override

query n vectors of dimension d to the index.

return all vectors with distance < radius. Note that many indexes do not implement the range_search (only the k-NN search is mandatory).

Parameters:

  • n – number of vectors

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

  • radius – search radius

  • result – result table

virtual void reconstruct(idx_t key, float *recons) const override

Reconstruct a stored vector (or an approximation if lossy coding)

this function may not be defined for some indexes

Parameters:

  • key – id of the vector to reconstruct

  • recons – reconstucted vector (size d)

virtual void reconstruct_n(idx_t i0, idx_t ni, float *recons) const override

Reconstruct vectors i0 to i0 + ni - 1

this function may not be defined for some indexes

Parameters:

  • i0 – index of the first vector in the sequence

  • ni – number of vectors in the sequence

  • recons – reconstucted vector (size ni * d)

virtual void search_and_reconstruct(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels, float *recons, const SearchParameters *params = nullptr) const override

Similar to search, but also reconstructs the stored vectors (or an approximation in the case of lossy coding) for the search results.

If there are not enough results for a query, the resulting arrays is padded with -1s.

Parameters:

  • n – number of vectors

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

  • k – number of extracted vectors

  • distances – output pairwise distances, size n*k

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

  • recons – reconstructed vectors size (n, k, d)

const float *apply_chain(idx_t n, const float *x) const

apply the transforms in the chain. The returned float * may be equal to x, otherwise it should be deallocated.

void reverse_chain(idx_t n, const float *xt, float *x) const

Reverse the transforms in the chain. May not be implemented for all transforms in the chain or may return approximate results.

virtual DistanceComputer *get_distance_computer() const override

Get a DistanceComputer (defined in AuxIndexStructures) object for this kind of index.

DistanceComputer is implemented for indexes that support random access of their vectors.

virtual size_t sa_code_size() const override

size of the produced codes in bytes

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

virtual void merge_from(Index &otherIndex, idx_t add_id = 0) override

moves the entries from another dataset to self. On output, other is empty. add_id is added to all moved ids (for sequential ids, this would be this->ntotal)

virtual void check_compatible_for_merge(const Index &otherIndex) const override

check that the two indexes are compatible (ie, they are trained in the same way and have the same parameters). Otherwise throw.

~IndexPreTransform() override

Public Members

std::vector<VectorTransform*> chain
Index *index

! chain of transforms

bool own_fields

! the sub-index