File IndexRefine.h
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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.
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)
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. 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.
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. This file contains callbacks for kernels that compute distances.
The SIMDResultHandler object is intended to be templated and inlined. Methods:
handle(): called when 32 distances are computed and provided in two simd16uint16. (q, b) indicate which entry it is in the block.
set_block_origin(): set the sub-matrix that is being computed
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.
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struct IndexRefine : public faiss::Index
- #include <IndexRefine.h>
Index that queries in a base_index (a fast one) and refines the results with an exact search, hopefully improving the results.
Subclassed by faiss::IndexRefineFlat
Public Functions
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IndexRefine()
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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
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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
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virtual void reset() override
removes all elements from the database.
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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
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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)
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virtual size_t sa_code_size() const override
size of the produced codes in bytes
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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()
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virtual void sa_decode(idx_t n, const uint8_t *bytes, float *x) const override
The sa_decode decodes from the index_refine, which is assumed to be more accurate
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~IndexRefine() override
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IndexRefine()
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struct IndexRefineFlat : public faiss::IndexRefine
- #include <IndexRefine.h>
Version where the refinement index is an IndexFlat. It has one additional constructor that takes a table of elements to add to the flat refinement index
Public Functions
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IndexRefineFlat()
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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
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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
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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
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virtual void reset() override
removes all elements from the database.
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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)
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virtual size_t sa_code_size() const override
size of the produced codes in bytes
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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()
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IndexRefineFlat()