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/*
* Copyright (c) Meta Platforms, Inc. and affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <cassert>
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <sys/stat.h>
#include <sys/time.h>
#include <faiss/AutoTune.h>
#include <faiss/index_factory.h>
/**
* To run this demo, please download the ANN_SIFT1M dataset from
*
* http://corpus-texmex.irisa.fr/
*
* and unzip it to the subdirectory sift1M.
**/
/*****************************************************
* I/O functions for fvecs and ivecs
*****************************************************/
float* fvecs_read(const char* fname, size_t* d_out, size_t* n_out) {
FILE* f = fopen(fname, "r");
if (!f) {
fprintf(stderr, "could not open %s\n", fname);
perror("");
abort();
}
int d;
fread(&d, 1, sizeof(int), f);
assert((d > 0 && d < 1000000) || !"unreasonable dimension");
fseek(f, 0, SEEK_SET);
struct stat st;
fstat(fileno(f), &st);
size_t sz = st.st_size;
assert(sz % ((d + 1) * 4) == 0 || !"weird file size");
size_t n = sz / ((d + 1) * 4);
*d_out = d;
*n_out = n;
float* x = new float[n * (d + 1)];
size_t nr __attribute__((unused)) = fread(x, sizeof(float), n * (d + 1), f);
assert(nr == n * (d + 1) || !"could not read whole file");
// shift array to remove row headers
for (size_t i = 0; i < n; i++)
memmove(x + i * d, x + 1 + i * (d + 1), d * sizeof(*x));
fclose(f);
return x;
}
// not very clean, but works as long as sizeof(int) == sizeof(float)
int* ivecs_read(const char* fname, size_t* d_out, size_t* n_out) {
return (int*)fvecs_read(fname, d_out, n_out);
}
double elapsed() {
struct timeval tv;
gettimeofday(&tv, nullptr);
return tv.tv_sec + tv.tv_usec * 1e-6;
}
int main() {
double t0 = elapsed();
// this is typically the fastest one.
const char* index_key = "IVF4096,Flat";
// these ones have better memory usage
// const char *index_key = "Flat";
// const char *index_key = "PQ32";
// const char *index_key = "PCA80,Flat";
// const char *index_key = "IVF4096,PQ8+16";
// const char *index_key = "IVF4096,PQ32";
// const char *index_key = "IMI2x8,PQ32";
// const char *index_key = "IMI2x8,PQ8+16";
// const char *index_key = "OPQ16_64,IMI2x8,PQ8+16";
faiss::Index* index;
size_t d;
{
printf("[%.3f s] Loading train set\n", elapsed() - t0);
size_t nt;
float* xt = fvecs_read("sift1M/sift_learn.fvecs", &d, &nt);
printf("[%.3f s] Preparing index \"%s\" d=%ld\n",
elapsed() - t0,
index_key,
d);
index = faiss::index_factory(d, index_key);
printf("[%.3f s] Training on %ld vectors\n", elapsed() - t0, nt);
index->train(nt, xt);
delete[] xt;
}
{
printf("[%.3f s] Loading database\n", elapsed() - t0);
size_t nb, d2;
float* xb = fvecs_read("sift1M/sift_base.fvecs", &d2, &nb);
assert(d == d2 || !"dataset does not have same dimension as train set");
printf("[%.3f s] Indexing database, size %ld*%ld\n",
elapsed() - t0,
nb,
d);
index->add(nb, xb);
delete[] xb;
}
size_t nq;
float* xq;
{
printf("[%.3f s] Loading queries\n", elapsed() - t0);
size_t d2;
xq = fvecs_read("sift1M/sift_query.fvecs", &d2, &nq);
assert(d == d2 || !"query does not have same dimension as train set");
}
size_t k; // nb of results per query in the GT
faiss::idx_t* gt; // nq * k matrix of ground-truth nearest-neighbors
{
printf("[%.3f s] Loading ground truth for %ld queries\n",
elapsed() - t0,
nq);
// load ground-truth and convert int to long
size_t nq2;
int* gt_int = ivecs_read("sift1M/sift_groundtruth.ivecs", &k, &nq2);
assert(nq2 == nq || !"incorrect nb of ground truth entries");
gt = new faiss::idx_t[k * nq];
for (int i = 0; i < k * nq; i++) {
gt[i] = gt_int[i];
}
delete[] gt_int;
}
// Result of the auto-tuning
std::string selected_params;
{ // run auto-tuning
printf("[%.3f s] Preparing auto-tune criterion 1-recall at 1 "
"criterion, with k=%ld nq=%ld\n",
elapsed() - t0,
k,
nq);
faiss::OneRecallAtRCriterion crit(nq, 1);
crit.set_groundtruth(k, nullptr, gt);
crit.nnn = k; // by default, the criterion will request only 1 NN
printf("[%.3f s] Preparing auto-tune parameters\n", elapsed() - t0);
faiss::ParameterSpace params;
params.initialize(index);
printf("[%.3f s] Auto-tuning over %ld parameters (%ld combinations)\n",
elapsed() - t0,
params.parameter_ranges.size(),
params.n_combinations());
faiss::OperatingPoints ops;
params.explore(index, nq, xq, crit, &ops);
printf("[%.3f s] Found the following operating points: \n",
elapsed() - t0);
ops.display();
// keep the first parameter that obtains > 0.5 1-recall@1
for (int i = 0; i < ops.optimal_pts.size(); i++) {
if (ops.optimal_pts[i].perf > 0.5) {
selected_params = ops.optimal_pts[i].key;
break;
}
}
assert(selected_params.size() >= 0 ||
!"could not find good enough op point");
}
{ // Use the found configuration to perform a search
faiss::ParameterSpace params;
printf("[%.3f s] Setting parameter configuration \"%s\" on index\n",
elapsed() - t0,
selected_params.c_str());
params.set_index_parameters(index, selected_params.c_str());
printf("[%.3f s] Perform a search on %ld queries\n",
elapsed() - t0,
nq);
// output buffers
faiss::idx_t* I = new faiss::idx_t[nq * k];
float* D = new float[nq * k];
index->search(nq, xq, k, D, I);
printf("[%.3f s] Compute recalls\n", elapsed() - t0);
// evaluate result by hand.
int n_1 = 0, n_10 = 0, n_100 = 0;
for (int i = 0; i < nq; i++) {
int gt_nn = gt[i * k];
for (int j = 0; j < k; j++) {
if (I[i * k + j] == gt_nn) {
if (j < 1)
n_1++;
if (j < 10)
n_10++;
if (j < 100)
n_100++;
}
}
}
printf("R@1 = %.4f\n", n_1 / float(nq));
printf("R@10 = %.4f\n", n_10 / float(nq));
printf("R@100 = %.4f\n", n_100 / float(nq));
delete[] I;
delete[] D;
}
delete[] xq;
delete[] gt;
delete index;
return 0;
}
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