File IndexShards.h
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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.
Typedefs
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using IndexShards = IndexShardsTemplate<Index>
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using IndexBinaryShards = IndexShardsTemplate<IndexBinary>
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template<typename IndexT>
struct IndexShardsTemplate : public faiss::ThreadedIndex<IndexT> - #include <IndexShards.h>
Index that concatenates the results from several sub-indexes
Subclassed by faiss::IndexShardsIVF
Public Types
Public Functions
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explicit IndexShardsTemplate(bool threaded = false, bool successive_ids = true)
The dimension that all sub-indices must share will be the dimension of the first sub-index added
- Parameters:
threaded – do we use one thread per sub_index or do queries sequentially?
successive_ids – should we shift the returned ids by the size of each sub-index or return them as they are?
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explicit IndexShardsTemplate(idx_t d, bool threaded = false, bool successive_ids = true)
- Parameters:
threaded – do we use one thread per sub_index or do queries sequentially?
successive_ids – should we shift the returned ids by the size of each sub-index or return them as they are?
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explicit IndexShardsTemplate(int d, bool threaded = false, bool successive_ids = true)
int version due to the implicit bool conversion ambiguity of int as dimension
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inline void add_shard(IndexT *index)
Alias for addIndex()
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inline void remove_shard(IndexT *index)
Alias for removeIndex()
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void add(idx_t n, const component_t *x) override
supported only for sub-indices that implement add_with_ids
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void add_with_ids(idx_t n, const component_t *x, const idx_t *xids) override
Cases (successive_ids, xids):
true, non-NULL ERROR: it makes no sense to pass in ids and request them to be shifted
true, NULL OK: but should be called only once (calls add() on sub-indexes).
false, non-NULL OK: will call add_with_ids with passed in xids distributed evenly over shards
false, NULL OK: will call add_with_ids on each sub-index, starting at ntotal
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void search(idx_t n, const component_t *x, idx_t k, distance_t *distances, idx_t *labels, const SearchParameters *params = nullptr) const override
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void train(idx_t n, const component_t *x) override
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virtual void syncWithSubIndexes()
Synchronize the top-level index (IndexShards) with data in the sub-indices
Public Members
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bool successive_ids
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explicit IndexShardsTemplate(bool threaded = false, bool successive_ids = true)
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using IndexShards = IndexShardsTemplate<Index>