/data/users/matthijs/github_faiss/faiss/IndexIVF.h

/**
 * Copyright (c) 2015-present, Facebook, Inc.
 * All rights reserved.
 *
 * This source code is licensed under the BSD+Patents license found in the
 * LICENSE file in the root directory of this source tree.
 */

// Copyright 2004-present Facebook. All Rights Reserved.
// -*- c++ -*-

#ifndef FAISS_INDEX_IVF_H
#define FAISS_INDEX_IVF_H


#include <vector>


#include "Index.h"
#include "Clustering.h"
#include "Heap.h"


namespace faiss {



/** 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 then stored.
 *
 * 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 {
    size_t nlist;             ///< number of possible key values
    size_t nprobe;            ///< number of probes at query time

    Index * quantizer;        ///< quantizer that maps vectors to inverted lists
    bool quantizer_trains_alone;   ///< just pass over the trainset to quantizer
    bool own_fields;          ///< whether object owns the quantizer

    ClusteringParameters cp; ///< to override default clustering params

    std::vector < std::vector<long> > ids;  ///< Inverted lists for indexes

    /// map for direct access to the elements. Enables reconstruct().
    bool maintain_direct_map;
    std::vector <long> 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,
              MetricType metric = METRIC_INNER_PRODUCT);

    void reset() override;

    /// Trains the quantizer and calls train_residual to train sub-quantizers
    void train(idx_t n, const float* x) override;

    /// Quantizes x and calls add_with_key
    void add(idx_t n, const float* x) override;

    /// 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);

    /** 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);

    /** implemented by sub-classes */
    virtual void merge_from_residuals (IndexIVF &other) = 0;

    ~IndexIVF() override;

    size_t get_list_size (size_t list_no) const
    { return ids[list_no].size(); }

    /** 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);

    /// 1= perfectly balanced, >1: imbalanced
    double imbalance_factor () const;

    /// display some stats about the inverted lists
    void print_stats () const;

    IndexIVF ();
};


struct IndexIVFFlatStats {
    size_t nq;       // nb of queries run
    size_t nlist;    // nb of inverted lists scanned
    size_t ndis;     // nb of distancs computed
    size_t npartial; // nb of bound computations (IndexIVFFlatIPBounds)

    IndexIVFFlatStats () {reset (); }
    void reset ();
};

// global var that collects them all
extern IndexIVFFlatStats indexIVFFlat_stats;





/** Inverted file with stored vectors. Here the inverted file
 * pre-selects the vectors to be searched, but they are not otherwise
 * encoded.
 */
struct IndexIVFFlat: IndexIVF {
    /** Inverted list of original vectors. Each list is a nl * d
     * matrix, where nl is the nb of vectors stored in the list. */
    std::vector < std::vector<float> > vecs;

    IndexIVFFlat (
            Index * quantizer, size_t d, size_t nlist_,
            MetricType = METRIC_INNER_PRODUCT);

    /// same as add_with_ids, with precomputed coarse quantizer
    virtual void add_core (idx_t n, const float * x, const long *xids,
                   const long *precomputed_idx);

    /// implemented for all IndexIVF* classes
    void add_with_ids(idx_t n, const float* x, const long* xids) override;

    void search(
        idx_t n,
        const float* x,
        idx_t k,
        float* distances,
        idx_t* labels) const override;

    /// perform search, without computing the assignment to the quantizer
    void search_preassigned (idx_t n, const float *x, idx_t k,
                             const idx_t *assign,
                             float *distances, idx_t *labels) const;

    void range_search(
        idx_t n,
        const float* x,
        float radius,
        RangeSearchResult* result) const override;

    /** 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
     */
    void copy_subset_to (IndexIVFFlat & other, int subset_type,
                         long a1, long a2) const;

    void reset() override;

    long remove_ids(const IDSelector& sel) override;

    /// Implementation of the search for the inner product metric
    void search_knn_inner_product (
            size_t nx, const float * x,
            const long * keys,
            float_minheap_array_t * res) const;

    /// Implementation of the search for the L2 metric
    void search_knn_L2sqr (
            size_t nx, const float * x,
            const long * keys,
            float_maxheap_array_t * res) const;

    /** Update a subset of vectors.
     *
     * The index must have a direct_map
     *
     * @param nv     nb of vectors to update
     * @param idx    vector indices to update, size nv
     * @param v      vectors of new values, size nv*d
     */
    void update_vectors (int nv, idx_t *idx, const float *v);

    void reconstruct(idx_t key, float* recons) const override;

    void merge_from_residuals(IndexIVF& other) override;

    IndexIVFFlat () {}
};

struct IndexIVFFlatIPBounds: IndexIVFFlat {

    /// nb of dimensions of pre-filter
    size_t fsize;

    /// norm of remainder (dimensions fsize:d)
    std::vector<std::vector<float> > part_norms;

    IndexIVFFlatIPBounds (
           Index * quantizer, size_t d, size_t nlist,
           size_t fsize);

    void add_core(
        idx_t n,
        const float* x,
        const long* xids,
        const long* precomputed_idx) override;

    void search(
        idx_t n,
        const float* x,
        idx_t k,
        float* distances,
        idx_t* labels) const override;
};



} // namespace faiss





#endif