File: IndexBinary_c.h

package info (click to toggle)
faiss 1.12.0-1
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 8,572 kB
  • sloc: cpp: 85,627; python: 27,889; sh: 905; ansic: 425; makefile: 41
file content (169 lines) | stat: -rw-r--r-- 5,022 bytes parent folder | download | duplicates (2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
/*
 * Copyright (c) Meta Platforms, Inc. and 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_BINARY_C_H
#define FAISS_INDEX_BINARY_C_H

#include <stddef.h>
#include "Index_c.h"
#include "faiss_c.h"

#ifdef __cplusplus
extern "C" {
#endif

// forward declaration required here
FAISS_DECLARE_CLASS(RangeSearchResult)

// typedef struct FaissRangeSearchResult_H FaissRangeSearchResult;
typedef struct FaissIDSelector_H FaissIDSelector;

/// Opaque type for referencing to a binary index object
FAISS_DECLARE_CLASS(IndexBinary)
FAISS_DECLARE_DESTRUCTOR(IndexBinary)

/// Getter for d
FAISS_DECLARE_GETTER(IndexBinary, int, d)

/// Getter for is_trained
FAISS_DECLARE_GETTER(IndexBinary, int, is_trained)

/// Getter for ntotal
FAISS_DECLARE_GETTER(IndexBinary, idx_t, ntotal)

/// Getter for metric_type
FAISS_DECLARE_GETTER(IndexBinary, FaissMetricType, metric_type)

FAISS_DECLARE_GETTER_SETTER(IndexBinary, int, verbose)

/** Perform training on a representative set of vectors
 *
 * @param index  opaque pointer to index object
 * @param n      nb of training vectors
 * @param x      training vectors, size n * d
 */
int faiss_IndexBinary_train(FaissIndexBinary* index, idx_t n, const uint8_t* x);

/** 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.
 * @param index  opaque pointer to index object
 * @param x      input matrix, size n * d
 */
int faiss_IndexBinary_add(FaissIndexBinary* index, idx_t n, const uint8_t* x);

/** Same as add, but stores xids instead of sequential ids.
 *
 * The default implementation fails with an assertion, as it is
 * not supported by all indexes.
 *
 * @param index  opaque pointer to index object
 * @param xids   if non-null, ids to store for the vectors (size n)
 */
int faiss_IndexBinary_add_with_ids(
        FaissIndexBinary* index,
        idx_t n,
        const uint8_t* x,
        const idx_t* xids);

/** 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.
 *
 * @param index       opaque pointer to index object
 * @param x           input vectors to search, size n * d
 * @param labels      output labels of the NNs, size n*k
 * @param distances   output pairwise distances, size n*k
 */
int faiss_IndexBinary_search(
        const FaissIndexBinary* index,
        idx_t n,
        const uint8_t* x,
        idx_t k,
        int32_t* distances,
        idx_t* labels);

/** query n vectors of dimension d to the index.
 *
 * return all vectors with distance < radius. Note that many
 * indexes do not implement the range_search (only the k-NN search
 * is mandatory).
 *
 * @param index       opaque pointer to index object
 * @param x           input vectors to search, size n * d
 * @param radius      search radius
 * @param result      result table
 */
int faiss_IndexBinary_range_search(
        const FaissIndexBinary* index,
        idx_t n,
        const uint8_t* x,
        int radius,
        FaissRangeSearchResult* result);

/** return the indexes of the k vectors closest to the query x.
 *
 * This function is identical as search but only return labels of neighbors.
 * @param index       opaque pointer to index object
 * @param x           input vectors to search, size n * d
 * @param labels      output labels of the NNs, size n*k
 */
int faiss_IndexBinary_assign(
        FaissIndexBinary* index,
        idx_t n,
        const uint8_t* x,
        idx_t* labels,
        idx_t k);

/** removes all elements from the database.
 * @param index       opaque pointer to index object
 */
int faiss_IndexBinary_reset(FaissIndexBinary* index);

/** removes IDs from the index. Not supported by all indexes
 * @param index       opaque pointer to index object
 * @param nremove     output for the number of IDs removed
 */
int faiss_IndexBinary_remove_ids(
        FaissIndexBinary* index,
        const FaissIDSelector* sel,
        size_t* n_removed);

/** Reconstruct a stored vector (or an approximation if lossy coding)
 *
 * this function may not be defined for some indexes
 * @param index       opaque pointer to index object
 * @param key         id of the vector to reconstruct
 * @param recons      reconstructed vector (size d)
 */
int faiss_IndexBinary_reconstruct(
        const FaissIndexBinary* index,
        idx_t key,
        uint8_t* recons);

/** Reconstruct vectors i0 to i0 + ni - 1
 *
 * this function may not be defined for some indexes
 * @param index       opaque pointer to index object
 * @param recons      reconstructed vector (size ni * d)
 */
int faiss_IndexBinary_reconstruct_n(
        const FaissIndexBinary* index,
        idx_t i0,
        idx_t ni,
        uint8_t* recons);

#ifdef __cplusplus
}
#endif

#endif