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WriteIndex.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 #include "../../IndexIVFFlat.h"
11 #include "../../IndexIVFPQ.h"
12 #include "../../IndexFlat.h"
13 #include "../../index_io.h"
14 #include "../test/TestUtils.h"
15 #include <vector>
16 #include <gflags/gflags.h>
17
18 // For IVFPQ:
19 DEFINE_bool(ivfpq, false, "use IVFPQ encoding");
20 DEFINE_int32(codes, 4, "number of PQ codes per vector");
21 DEFINE_int32(bits_per_code, 8, "number of bits per PQ code");
22
23 // For IVFFlat:
24 DEFINE_bool(l2, true, "use L2 metric (versus IP metric)");
25 DEFINE_bool(ivfflat, false, "use IVF flat encoding");
26
27 // For both:
28 DEFINE_string(out, "/home/jhj/local/index.out", "index file for output");
29 DEFINE_int32(dim, 128, "vector dimension");
30 DEFINE_int32(num_coarse, 100, "number of coarse centroids");
31 DEFINE_int32(num, 100000, "total database size");
32 DEFINE_int32(num_train, -1, "number of database vecs to train on");
33
34 template <typename T>
35 void fillAndSave(T& index, int numTrain, int num, int dim) {
36 auto trainVecs = faiss::gpu::randVecs(numTrain, dim);
37 index.train(numTrain, trainVecs.data());
38
39 constexpr int kAddChunk = 1000000;
40
41 for (int i = 0; i < num; i += kAddChunk) {
42 int numRemaining = (num - i) < kAddChunk ? (num - i) : kAddChunk;
43 auto vecs = faiss::gpu::randVecs(numRemaining, dim);
44
45 printf("adding at %d: %d\n", i, numRemaining);
46 index.add(numRemaining, vecs.data());
47 }
48
49 faiss::write_index(&index, FLAGS_out.c_str());
50 }
51
52 int main(int argc, char** argv) {
53 gflags::ParseCommandLineFlags(&argc, &argv, true);
54
55 // Either ivfpq or ivfflat must be set
56 if ((FLAGS_ivfpq && FLAGS_ivfflat) ||
57 (!FLAGS_ivfpq && !FLAGS_ivfflat)) {
58 printf("must specify either ivfpq or ivfflat\n");
59 return 1;
60 }
61
62 auto dim = FLAGS_dim;
63 auto numCentroids = FLAGS_num_coarse;
64 auto num = FLAGS_num;
65 auto numTrain = FLAGS_num_train;
66 numTrain = numTrain == -1 ? std::max((num / 4), 1) : numTrain;
67 numTrain = std::min(num, numTrain);
68
69 if (FLAGS_ivfpq) {
70 faiss::IndexFlatL2 quantizer(dim);
71 faiss::IndexIVFPQ index(&quantizer, dim, numCentroids,
72 FLAGS_codes, FLAGS_bits_per_code);
73 index.verbose = true;
74
75 printf("IVFPQ: codes %d bits per code %d\n",
76 FLAGS_codes, FLAGS_bits_per_code);
77 printf("Lists: %d\n", numCentroids);
78 printf("Database: dim %d num vecs %d trained on %d\n", dim, num, numTrain);
79 printf("output file: %s\n", FLAGS_out.c_str());
80
81 fillAndSave(index, numTrain, num, dim);
82 } else if (FLAGS_ivfflat) {
83 faiss::IndexFlatL2 quantizerL2(dim);
84 faiss::IndexFlatIP quantizerIP(dim);
85
86 faiss::IndexFlat* quantizer = FLAGS_l2 ?
87 (faiss::IndexFlat*) &quantizerL2 :
88 (faiss::IndexFlat*) &quantizerIP;
89
90 faiss::IndexIVFFlat index(quantizer, dim, numCentroids,
91 FLAGS_l2 ? faiss::METRIC_L2 :
92 faiss::METRIC_INNER_PRODUCT);
93
94 printf("IVFFlat: metric %s\n", FLAGS_l2 ? "L2" : "IP");
95 printf("Lists: %d\n", numCentroids);
96 printf("Database: dim %d num vecs %d trained on %d\n", dim, num, numTrain);
97 printf("output file: %s\n", FLAGS_out.c_str());
98
99 fillAndSave(index, numTrain, num, dim);
100 }
101
102 return 0;
103 }
faiss::IndexFlat
Definition: IndexFlat.h:22
faiss::IndexFlatL2
Definition: IndexFlat.h:78
faiss::IndexIVFFlat
Definition: IndexIVFFlat.h:25
faiss::IndexFlatIP
Definition: IndexFlat.h:72
faiss::IndexIVFPQ
Definition: IndexIVFPQ.h:35