File IndexIVFPQR.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 IndexIVFPQR : public faiss::IndexIVFPQ
#include <IndexIVFPQR.h>

Index with an additional level of PQ refinement

Public Functions

IndexIVFPQR(Index *quantizer, size_t d, size_t nlist, size_t M, size_t nbits_per_idx, size_t M_refine, size_t nbits_per_idx_refine)
virtual void reset() override

removes all elements from the database.

virtual size_t remove_ids(const IDSelector &sel) override

Dataset manipulation functions.

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

trains the two product quantizers

virtual idx_t train_encoder_num_vectors() const override

can be redefined by subclasses to indicate how many training vectors they need

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

default implementation that calls encode_vectors

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

same as add_with_ids, but optionally use the precomputed list ids

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 merge_from(Index &otherIndex, idx_t add_id) 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 search_preassigned(idx_t n, const float *x, idx_t k, const idx_t *assign, const float *centroid_dis, float *distances, idx_t *labels, bool store_pairs, const IVFSearchParameters *params = nullptr, IndexIVFStats *stats = nullptr) const override

search a set of vectors, that are pre-quantized by the IVF quantizer. Fill in the corresponding heaps with the query results. The default implementation uses InvertedListScanners to do the search.

Parameters:

  • n – nb of vectors to query

  • x – query vectors, size nx * d

  • assign – coarse quantization indices, size nx * nprobe

  • centroid_dis – distances to coarse centroids, size nx * nprobe

  • distance – output distances, size n * k

  • labels – output labels, size n * k

  • store_pairs – store inv list index + inv list offset instead in upper/lower 32 bit of result, instead of ids (used for reranking).

  • params – used to override the object’s search parameters

  • stats – search stats to be updated (can be null)

IndexIVFPQR()

Public Members

ProductQuantizer refine_pq

3rd level quantizer

std::vector<uint8_t> refine_codes

corresponding codes

float k_factor

factor between k requested in search and the k requested from the IVFPQ