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