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test_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 #include <cstdio>
12 #include <cstdlib>
13
14 #include <gtest/gtest.h>
15
16 #include <IndexIVFPQ.h>
17 #include <IndexFlat.h>
18 #include <index_io.h>
19
20 TEST(IVFPQ, accuracy) {
21
22 // dimension of the vectors to index
23 int d = 64;
24
25 // size of the database we plan to index
26 size_t nb = 1000;
27
28 // make a set of nt training vectors in the unit cube
29 // (could be the database)
30 size_t nt = 1500;
31
32 // make the index object and train it
33 faiss::IndexFlatL2 coarse_quantizer (d);
34
35 // a reasonable number of cetroids to index nb vectors
36 int ncentroids = 25;
37
38 faiss::IndexIVFPQ index (&coarse_quantizer, d,
39 ncentroids, 16, 8);
40
41 // index that gives the ground-truth
42 faiss::IndexFlatL2 index_gt (d);
43
44 srand48 (35);
45
46 { // training
47
48 std::vector <float> trainvecs (nt * d);
49 for (size_t i = 0; i < nt * d; i++) {
50 trainvecs[i] = drand48();
51 }
52 index.verbose = true;
53 index.train (nt, trainvecs.data());
54 }
55
56 { // populating the database
57
58 std::vector <float> database (nb * d);
59 for (size_t i = 0; i < nb * d; i++) {
60 database[i] = drand48();
61 }
62
63 index.add (nb, database.data());
64 index_gt.add (nb, database.data());
65 }
66
67 int nq = 200;
68 int n_ok;
69
70 { // searching the database
71
72 std::vector <float> queries (nq * d);
73 for (size_t i = 0; i < nq * d; i++) {
74 queries[i] = drand48();
75 }
76
77 std::vector<faiss::Index::idx_t> gt_nns (nq);
78 std::vector<float> gt_dis (nq);
79
80 index_gt.search (nq, queries.data(), 1,
81 gt_dis.data(), gt_nns.data());
82
83 index.nprobe = 5;
84 int k = 5;
85 std::vector<faiss::Index::idx_t> nns (k * nq);
86 std::vector<float> dis (k * nq);
87
88 index.search (nq, queries.data(), k, dis.data(), nns.data());
89
90 n_ok = 0;
91 for (int q = 0; q < nq; q++) {
92
93 for (int i = 0; i < k; i++)
94 if (nns[q * k + i] == gt_nns[q])
95 n_ok++;
96 }
97 EXPECT_GT(n_ok, nq * 0.4);
98 }
99
100 }
faiss::IndexFlatL2
Definition: IndexFlat.h:79
faiss::IndexIVFPQ
Definition: IndexIVFPQ.h:29