File IndexRowwiseMinMax.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 int rowwise_minmax_sa_encode_bs

block size for performing sa_encode and sa_decode

FAISS_API int rowwise_minmax_sa_decode_bs
struct IndexRowwiseMinMax : public faiss::IndexRowwiseMinMaxBase
#include <IndexRowwiseMinMax.h>

Stores scaling coefficients as fp32 values.

Public Functions

explicit IndexRowwiseMinMax(Index *index)
IndexRowwiseMinMax()
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 train_inplace(idx_t n, float *x) override
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 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 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:
  • 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 void reset() override

removes all elements from the database.

Public Members

Index *index

sub-index

bool own_fields

whether the subindex needs to be freed in the destructor.

struct IndexRowwiseMinMaxBase : public faiss::Index
#include <IndexRowwiseMinMax.h>

Provides base functions for rowwise normalizing indices.

Index wrapper that performs rowwise normalization to [0,1], preserving the coefficients. This is a vector codec index only.

Basically, this index performs a rowwise scaling to [0,1] of every row in an input dataset before calling subindex::train() and subindex::sa_encode(). sa_encode() call stores the scaling coefficients (scaler and minv) in the very beginning of every output code. The format: [scaler][minv][subindex::sa_encode() output] The de-scaling in sa_decode() is done using: output_rescaled = scaler * output + minv

An additional ::train_inplace() function is provided in order to do an inplace scaling before calling subindex::train() and, thus, avoiding the cloning of the input dataset, but modifying the input dataset because of the scaling and the scaling back. It is up to user to call this function instead of ::train()

Derived classes provide different data types for scaling coefficients. Currently, versions with fp16 and fp32 scaling coefficients are available.

  • fp16 version adds 4 extra bytes per encoded vector

  • fp32 version adds 8 extra bytes per encoded vector

Subclassed by faiss::IndexRowwiseMinMax, faiss::IndexRowwiseMinMaxFP16

Public Functions

explicit IndexRowwiseMinMaxBase(Index *index)
IndexRowwiseMinMaxBase()
~IndexRowwiseMinMaxBase() override
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 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:
  • 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 void reset() override

removes all elements from the database.

virtual void train_inplace(idx_t n, float *x) = 0

Public Members

Index *index

sub-index

bool own_fields

whether the subindex needs to be freed in the destructor.

struct IndexRowwiseMinMaxFP16 : public faiss::IndexRowwiseMinMaxBase
#include <IndexRowwiseMinMax.h>

Stores scaling coefficients as fp16 values.

Public Functions

explicit IndexRowwiseMinMaxFP16(Index *index)
IndexRowwiseMinMaxFP16()
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 train_inplace(idx_t n, float *x) override
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 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 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:
  • 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 void reset() override

removes all elements from the database.

Public Members

Index *index

sub-index

bool own_fields

whether the subindex needs to be freed in the destructor.