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demo_ivfpq_indexing.cpp
1
2 /**
3 * Copyright (c) 2015-present, Facebook, Inc.
4 * All rights reserved.
5 *
6 * This source code is licensed under the CC-by-NC license found in the
7 * LICENSE file in the root directory of this source tree.
8 */
9
10 // Copyright 2004-present Facebook. All Rights Reserved
11
12
13 #include <cmath>
14 #include <cstdio>
15 #include <cstdlib>
16
17 #include <sys/time.h>
18
19
20 #include "../IndexIVFPQ.h"
21 #include "../IndexFlat.h"
22 #include "../index_io.h"
23
24 double elapsed ()
25 {
26 struct timeval tv;
27 gettimeofday (&tv, NULL);
28 return tv.tv_sec + tv.tv_usec * 1e-6;
29 }
30
31
32 int main ()
33 {
34
35 double t0 = elapsed();
36
37 // dimension of the vectors to index
38 int d = 128;
39
40 // size of the database we plan to index
41 size_t nb = 200 * 1000;
42
43 // make a set of nt training vectors in the unit cube
44 // (could be the database)
45 size_t nt = 100 * 1000;
46
47 // make the index object and train it
48 faiss::IndexFlatL2 coarse_quantizer (d);
49
50 // a reasonable number of centroids to index nb vectors
51 int ncentroids = int (4 * sqrt (nb));
52
53 // the coarse quantizer should not be dealloced before the index
54 // 4 = nb of bytes per code (d must be a multiple of this)
55 // 8 = nb of bits per sub-code (almost always 8)
56 faiss::IndexIVFPQ index (&coarse_quantizer, d,
57 ncentroids, 4, 8);
58
59
60 { // training
61 printf ("[%.3f s] Generating %ld vectors in %dD for training\n",
62 elapsed() - t0, nt, d);
63
64 std::vector <float> trainvecs (nt * d);
65 for (size_t i = 0; i < nt * d; i++) {
66 trainvecs[i] = drand48();
67 }
68
69 printf ("[%.3f s] Training the index\n",
70 elapsed() - t0);
71 index.verbose = true;
72
73 index.train (nt, trainvecs.data());
74 }
75
76 { // I/O demo
77 const char *outfilename = "/tmp/index_trained.faissindex";
78 printf ("[%.3f s] storing the pre-trained index to %s\n",
79 elapsed() - t0, outfilename);
80
81 write_index (&index, outfilename);
82 }
83
84 size_t nq;
85 std::vector<float> queries;
86
87 { // populating the database
88 printf ("[%.3f s] Building a dataset of %ld vectors to index\n",
89 elapsed() - t0, nb);
90
91 std::vector <float> database (nb * d);
92 for (size_t i = 0; i < nb * d; i++) {
93 database[i] = drand48();
94 }
95
96 printf ("[%.3f s] Adding the vectors to the index\n",
97 elapsed() - t0);
98
99 index.add (nb, database.data());
100
101 printf ("[%.3f s] imbalance factor: %g\n",
102 elapsed() - t0, index.imbalance_factor ());
103
104 // remember a few elements from the database as queries
105 int i0 = 1234;
106 int i1 = 1243;
107
108 nq = i1 - i0;
109 queries.resize (nq * d);
110 for (int i = i0; i < i1; i++) {
111 for (int j = 0; j < d; j++) {
112 queries [(i - i0) * d + j] = database [i * d + j];
113 }
114 }
115
116 }
117
118 { // searching the database
119 int k = 5;
120 printf ("[%.3f s] Searching the %d nearest neighbors "
121 "of %ld vectors in the index\n",
122 elapsed() - t0, k, nq);
123
124 std::vector<faiss::Index::idx_t> nns (k * nq);
125 std::vector<float> dis (k * nq);
126
127 index.search (nq, queries.data(), k, dis.data(), nns.data());
128
129 printf ("[%.3f s] Query results (vector ids, then distances):\n",
130 elapsed() - t0);
131
132 for (int i = 0; i < nq; i++) {
133 printf ("query %2d: ", i);
134 for (int j = 0; j < k; j++) {
135 printf ("%7ld ", nns[j + i * k]);
136 }
137 printf ("\n dis: ");
138 for (int j = 0; j < k; j++) {
139 printf ("%7g ", dis[j + i * k]);
140 }
141 printf ("\n");
142 }
143
144 printf ("note that the nearest neighbor is not at "
145 "distance 0 due to quantization errors\n");
146 }
147
148 return 0;
149 }
faiss::IndexFlatL2
Definition: IndexFlat.h:81
faiss::IndexIVFPQ
Definition: IndexIVFPQ.h:30