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demo_ivfpq_indexing.cpp
1 /**
2 * Copyright (c) 2015-present, Facebook, Inc.
3 * All rights reserved.
4 *
5 * This source code is licensed under the BSD+Patents license found in the
6 * LICENSE file in the root directory of this source tree.
7 */
8
9 // Copyright 2004-present Facebook. All Rights Reserved
10
11
12 #include <cmath>
13 #include <cstdio>
14 #include <cstdlib>
15
16 #include <sys/time.h>
17
18
19 #include "../IndexIVFPQ.h"
20 #include "../IndexFlat.h"
21 #include "../index_io.h"
22
23 double elapsed ()
24 {
25 struct timeval tv;
26 gettimeofday (&tv, NULL);
27 return tv.tv_sec + tv.tv_usec * 1e-6;
28 }
29
30
31 int main ()
32 {
33
34 double t0 = elapsed();
35
36 // dimension of the vectors to index
37 int d = 128;
38
39 // size of the database we plan to index
40 size_t nb = 200 * 1000;
41
42 // make a set of nt training vectors in the unit cube
43 // (could be the database)
44 size_t nt = 100 * 1000;
45
46 // make the index object and train it
47 faiss::IndexFlatL2 coarse_quantizer (d);
48
49 // a reasonable number of centroids to index nb vectors
50 int ncentroids = int (4 * sqrt (nb));
51
52 // the coarse quantizer should not be dealloced before the index
53 // 4 = nb of bytes per code (d must be a multiple of this)
54 // 8 = nb of bits per sub-code (almost always 8)
55 faiss::IndexIVFPQ index (&coarse_quantizer, d,
56 ncentroids, 4, 8);
57
58
59 { // training
60 printf ("[%.3f s] Generating %ld vectors in %dD for training\n",
61 elapsed() - t0, nt, d);
62
63 std::vector <float> trainvecs (nt * d);
64 for (size_t i = 0; i < nt * d; i++) {
65 trainvecs[i] = drand48();
66 }
67
68 printf ("[%.3f s] Training the index\n",
69 elapsed() - t0);
70 index.verbose = true;
71
72 index.train (nt, trainvecs.data());
73 }
74
75 { // I/O demo
76 const char *outfilename = "/tmp/index_trained.faissindex";
77 printf ("[%.3f s] storing the pre-trained index to %s\n",
78 elapsed() - t0, outfilename);
79
80 write_index (&index, outfilename);
81 }
82
83 size_t nq;
84 std::vector<float> queries;
85
86 { // populating the database
87 printf ("[%.3f s] Building a dataset of %ld vectors to index\n",
88 elapsed() - t0, nb);
89
90 std::vector <float> database (nb * d);
91 for (size_t i = 0; i < nb * d; i++) {
92 database[i] = drand48();
93 }
94
95 printf ("[%.3f s] Adding the vectors to the index\n",
96 elapsed() - t0);
97
98 index.add (nb, database.data());
99
100 printf ("[%.3f s] imbalance factor: %g\n",
101 elapsed() - t0, index.imbalance_factor ());
102
103 // remember a few elements from the database as queries
104 int i0 = 1234;
105 int i1 = 1243;
106
107 nq = i1 - i0;
108 queries.resize (nq * d);
109 for (int i = i0; i < i1; i++) {
110 for (int j = 0; j < d; j++) {
111 queries [(i - i0) * d + j] = database [i * d + j];
112 }
113 }
114
115 }
116
117 { // searching the database
118 int k = 5;
119 printf ("[%.3f s] Searching the %d nearest neighbors "
120 "of %ld vectors in the index\n",
121 elapsed() - t0, k, nq);
122
123 std::vector<faiss::Index::idx_t> nns (k * nq);
124 std::vector<float> dis (k * nq);
125
126 index.search (nq, queries.data(), k, dis.data(), nns.data());
127
128 printf ("[%.3f s] Query results (vector ids, then distances):\n",
129 elapsed() - t0);
130
131 for (int i = 0; i < nq; i++) {
132 printf ("query %2d: ", i);
133 for (int j = 0; j < k; j++) {
134 printf ("%7ld ", nns[j + i * k]);
135 }
136 printf ("\n dis: ");
137 for (int j = 0; j < k; j++) {
138 printf ("%7g ", dis[j + i * k]);
139 }
140 printf ("\n");
141 }
142
143 printf ("note that the nearest neighbor is not at "
144 "distance 0 due to quantization errors\n");
145 }
146
147 return 0;
148 }
faiss::IndexFlatL2
Definition: IndexFlat.h:79
faiss::IndexIVFPQ
Definition: IndexIVFPQ.h:29