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IndexIVF.h
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IndexIVF.h
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/**
* 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.
*/
// -*- c++ -*-
#ifndef FAISS_INDEX_IVF_H
#define FAISS_INDEX_IVF_H
#include <vector>
#include "Index.h"
#include "InvertedLists.h"
#include "Clustering.h"
#include "Heap.h"
namespace faiss {
/** Encapsulates a quantizer object for the IndexIVF
*
* The class isolates the fields that are independent of the storage
* of the lists (especially training)
*/
struct Level1Quantizer {
Index * quantizer; ///< quantizer that maps vectors to inverted lists
size_t nlist; ///< number of possible key values
/**
* = 0: use the quantizer as index in a kmeans training
* = 1: just pass on the training set to the train() of the quantizer
* = 2: kmeans training on a flat index + add the centroids to the quantizer
*/
char quantizer_trains_alone;
bool own_fields; ///< whether object owns the quantizer
ClusteringParameters cp; ///< to override default clustering params
Index *clustering_index; ///< to override index used during clustering
/// Trains the quantizer and calls train_residual to train sub-quantizers
void train_q1 (size_t n, const float *x, bool verbose,
MetricType metric_type);
Level1Quantizer (Index * quantizer, size_t nlist);
Level1Quantizer ();
~Level1Quantizer ();
};
struct IVFSearchParameters {
size_t nprobe; ///< number of probes at query time
size_t max_codes; ///< max nb of codes to visit to do a query
virtual ~IVFSearchParameters () {}
};
struct InvertedListScanner;
/** Index based on a inverted file (IVF)
*
* In the inverted file, the quantizer (an Index instance) provides a
* quantization index for each vector to be added. The quantization
* index maps to a list (aka inverted list or posting list), where the
* id of the vector is stored.
*
* The inverted list object is required only after trainng. If none is
* set externally, an ArrayInvertedLists is used automatically.
*
* At search time, the vector to be searched is also quantized, and
* only the list corresponding to the quantization index is
* searched. This speeds up the search by making it
* non-exhaustive. This can be relaxed using multi-probe search: a few
* (nprobe) quantization indices are selected and several inverted
* lists are visited.
*
* Sub-classes implement a post-filtering of the index that refines
* the distance estimation from the query to databse vectors.
*/
struct IndexIVF: Index, Level1Quantizer {
/// Acess to the actual data
InvertedLists *invlists;
bool own_invlists;
size_t code_size; ///< code size per vector in bytes
size_t nprobe; ///< number of probes at query time
size_t max_codes; ///< max nb of codes to visit to do a query
/** Parallel mode determines how queries are parallelized with OpenMP
*
* 0 (default): parallelize over queries
* 1: parallelize over over inverted lists
* 2: parallelize over both
*/
int parallel_mode;
/// map for direct access to the elements. Enables reconstruct().
bool maintain_direct_map;
std::vector <idx_t> direct_map;
/** The Inverted file takes a quantizer (an Index) on input,
* which implements the function mapping a vector to a list
* identifier. The pointer is borrowed: the quantizer should not
* be deleted while the IndexIVF is in use.
*/
IndexIVF (Index * quantizer, size_t d,
size_t nlist, size_t code_size,
MetricType metric = METRIC_L2);
void reset() override;
/// Trains the quantizer and calls train_residual to train sub-quantizers
void train(idx_t n, const float* x) override;
/// Calls add_with_ids with NULL ids
void add(idx_t n, const float* x) override;
/// default implementation that calls encode_vectors
void add_with_ids(idx_t n, const float* x, const idx_t* xids) override;
/** Encodes a set of vectors as they would appear in the inverted lists
*
* @param list_nos inverted list ids as returned by the
* quantizer (size n). -1s are ignored.
* @param codes output codes, size n * code_size
*/
virtual void encode_vectors(idx_t n, const float* x,
const idx_t *list_nos,
uint8_t * codes) const = 0;
/// Sub-classes that encode the residuals can train their encoders here
/// does nothing by default
virtual void train_residual (idx_t n, const float *x);
/** 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.
*
* @param n nb of vectors to query
* @param x query vectors, size nx * d
* @param assign coarse quantization indices, size nx * nprobe
* @param centroid_dis
* distances to coarse centroids, size nx * nprobe
* @param distance
* output distances, size n * k
* @param labels output labels, size n * k
* @param store_pairs store inv list index + inv list offset
* instead in upper/lower 32 bit of result,
* instead of ids (used for reranking).
* @param params used to override the object's search parameters
*/
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
) const;
/** assign the vectors, then call search_preassign */
void search (idx_t n, const float *x, idx_t k,
float *distances, idx_t *labels) const override;
void range_search (idx_t n, const float* x, float radius,
RangeSearchResult* result) const override;
void range_search_preassigned(idx_t nx, const float *x, float radius,
const idx_t *keys, const float *coarse_dis,
RangeSearchResult *result) const;
/// get a scanner for this index (store_pairs means ignore labels)
virtual InvertedListScanner *get_InvertedListScanner (
bool store_pairs=false) const;
void reconstruct (idx_t key, float* recons) const override;
/** Reconstruct a subset of the indexed vectors.
*
* Overrides default implementation to bypass reconstruct() which requires
* direct_map to be maintained.
*
* @param i0 first vector to reconstruct
* @param ni nb of vectors to reconstruct
* @param recons output array of reconstructed vectors, size ni * d
*/
void reconstruct_n(idx_t i0, idx_t ni, float* recons) const override;
/** Similar to search, but also reconstructs the stored vectors (or an
* approximation in the case of lossy coding) for the search results.
*
* Overrides default implementation to avoid having to maintain direct_map
* and instead fetch the code offsets through the `store_pairs` flag in
* search_preassigned().
*
* @param recons reconstructed vectors size (n, k, d)
*/
void search_and_reconstruct (idx_t n, const float *x, idx_t k,
float *distances, idx_t *labels,
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 reconstruct_from_offset (idx_t list_no, idx_t offset,
float* recons) const;
/// Dataset manipulation functions
idx_t remove_ids(const IDSelector& sel) override;
/** check that the two indexes are compatible (ie, they are
* trained in the same way and have the same
* parameters). Otherwise throw. */
void check_compatible_for_merge (const IndexIVF &other) const;
/** 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 merge_from (IndexIVF &other, idx_t add_id);
/** copy a subset of the entries index to the other index
*
* if subset_type == 0: copies ids in [a1, a2)
* if subset_type == 1: copies ids if id % a1 == a2
* if subset_type == 2: copies inverted lists such that a1
* elements are left before and a2 elements are after
*/
virtual void copy_subset_to (IndexIVF & other, int subset_type,
idx_t a1, idx_t a2) const;
~IndexIVF() override;
size_t get_list_size (size_t list_no) const
{ return invlists->list_size(list_no); }
/** intialize a direct map
*
* @param new_maintain_direct_map if true, create a direct map,
* else clear it
*/
void make_direct_map (bool new_maintain_direct_map=true);
/// replace the inverted lists, old one is deallocated if own_invlists
void replace_invlists (InvertedLists *il, bool own=false);
IndexIVF ();
};
struct RangeQueryResult;
/** Object that handles a query. The inverted lists to scan are
* provided externally. The object has a lot of state, but
* distance_to_code and scan_codes can be called in multiple
* threads */
struct InvertedListScanner {
using idx_t = Index::idx_t;
/// from now on we handle this query.
virtual void set_query (const float *query_vector) = 0;
/// following codes come from this inverted list
virtual void set_list (idx_t list_no, float coarse_dis) = 0;
/// compute a single query-to-code distance
virtual float distance_to_code (const uint8_t *code) const = 0;
/** scan a set of codes, compute distances to current query and
* update heap of results if necessary.
*
* @param n number of codes to scan
* @param codes codes to scan (n * code_size)
* @param ids corresponding ids (ignored if store_pairs)
* @param distances heap distances (size k)
* @param labels heap labels (size k)
* @param k heap size
* @return number of heap updates performed
*/
virtual size_t scan_codes (size_t n,
const uint8_t *codes,
const idx_t *ids,
float *distances, idx_t *labels,
size_t k) const = 0;
/** scan a set of codes, compute distances to current query and
* update results if distances are below radius
*
* (default implementation fails) */
virtual void scan_codes_range (size_t n,
const uint8_t *codes,
const idx_t *ids,
float radius,
RangeQueryResult &result) const;
virtual ~InvertedListScanner () {}
};
struct IndexIVFStats {
size_t nq; // nb of queries run
size_t nlist; // nb of inverted lists scanned
size_t ndis; // nb of distancs computed
size_t nheap_updates; // nb of times the heap was updated
double quantization_time; // time spent quantizing vectors (in ms)
double search_time; // time spent searching lists (in ms)
IndexIVFStats () {reset (); }
void reset ();
};
// global var that collects them all
extern IndexIVFStats indexIVF_stats;
extern int lola;
} // namespace faiss
#endif