File MatrixStats.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 MatrixStats
#include <MatrixStats.h>

Reports some statistics on a dataset and comments on them.

It is a class rather than a function so that all stats can also be accessed from code

Public Functions

MatrixStats(size_t n, size_t d, const float *x)
void do_comment(const char *fmt, ...)

Public Members

std::string comments
size_t n = 0
size_t d = 0
size_t n_collision = 0
size_t n_valid = 0
size_t n0 = 0
double min_norm2 = HUGE_VALF
double max_norm2 = 0
uint64_t hash_value = 0
std::vector<PerDimStats> per_dim_stats
std::unordered_map<uint64_t, Occurrence> occurrences
char *buf
size_t nbuf
struct Occurrence

Public Members

size_t first
size_t count
struct PerDimStats

Public Functions

void add(float x)
void compute_mean_std()

Public Members

size_t n = 0

counts of various special entries

size_t n_nan = 0
size_t n_inf = 0
size_t n0 = 0
float min = HUGE_VALF

to get min/max and stddev values

float max = -HUGE_VALF
double sum = 0
double sum2 = 0
size_t n_valid = 0
double mean = NAN
double stddev = NAN