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/data/users/matthijs/github_faiss/faiss/AutoTune.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 implementation of Hyper-parameter auto-tuning
11 */
12
13 #include "AutoTune.h"
14
15 #include "FaissAssert.h"
16 #include "utils.h"
17
18 #include "IndexFlat.h"
19 #include "VectorTransform.h"
20 #include "IndexLSH.h"
21 #include "IndexPQ.h"
22 #include "IndexIVF.h"
23 #include "IndexIVFPQ.h"
24 #include "MetaIndexes.h"
25 #include "IndexScalarQuantizer.h"
26
27
28 namespace faiss {
29
30
31 AutoTuneCriterion::AutoTuneCriterion (idx_t nq, idx_t nnn):
32 nq (nq), nnn (nnn), gt_nnn (0)
33 {}
34
35
36 void AutoTuneCriterion::set_groundtruth (
37 int gt_nnn, const float *gt_D_in, const idx_t *gt_I_in)
38 {
39 this->gt_nnn = gt_nnn;
40 if (gt_D_in) { // allow null for this, as it is often not used
41 gt_D.resize (nq * gt_nnn);
42 memcpy (gt_D.data(), gt_D_in, sizeof (gt_D[0]) * nq * gt_nnn);
43 }
44 gt_I.resize (nq * gt_nnn);
45 memcpy (gt_I.data(), gt_I_in, sizeof (gt_I[0]) * nq * gt_nnn);
46 }
47
48
49
50 OneRecallAtRCriterion::OneRecallAtRCriterion (idx_t nq, idx_t R):
51 AutoTuneCriterion(nq, R), R(R)
52 {}
53
54 double OneRecallAtRCriterion::evaluate(const float* /*D*/, const idx_t* I)
55 const {
56 FAISS_THROW_IF_NOT_MSG(
57 (gt_I.size() == gt_nnn * nq && gt_nnn >= 1 && nnn >= R),
58 "ground truth not initialized");
59 idx_t n_ok = 0;
60 for (idx_t q = 0; q < nq; q++) {
61 idx_t gt_nn = gt_I[q * gt_nnn];
62 const idx_t* I_line = I + q * nnn;
63 for (int i = 0; i < R; i++) {
64 if (I_line[i] == gt_nn) {
65 n_ok++;
66 break;
67 }
68 }
69 }
70 return n_ok / double(nq);
71 }
72
73
74 IntersectionCriterion::IntersectionCriterion (idx_t nq, idx_t R):
75 AutoTuneCriterion(nq, R), R(R)
76 {}
77
78 double IntersectionCriterion::evaluate(const float* /*D*/, const idx_t* I)
79 const {
80 FAISS_THROW_IF_NOT_MSG(
81 (gt_I.size() == gt_nnn * nq && gt_nnn >= R && nnn >= R),
82 "ground truth not initialized");
83 long n_ok = 0;
84 #pragma omp parallel for reduction(+: n_ok)
85 for (idx_t q = 0; q < nq; q++) {
86 n_ok += ranklist_intersection_size (
87 R, &gt_I [q * gt_nnn],
88 R, I + q * nnn);
89 }
90 return n_ok / double (nq * R);
91 }
92
93 /***************************************************************
94 * OperatingPoints
95 ***************************************************************/
96
97 OperatingPoints::OperatingPoints ()
98 {
99 clear();
100 }
101
102 void OperatingPoints::clear ()
103 {
104 all_pts.clear();
105 optimal_pts.clear();
106 /// default point: doing nothing gives 0 performance and takes 0 time
107 OperatingPoint op = {0, 0, "", -1};
108 optimal_pts.push_back(op);
109 }
110
111 /// add a performance measure
112 bool OperatingPoints::add (double perf, double t, const std::string & key,
113 size_t cno)
114 {
115 OperatingPoint op = {perf, t, key, long(cno)};
116 all_pts.push_back (op);
117 if (perf == 0) {
118 return false; // no method for 0 accuracy is faster than doing nothing
119 }
120 std::vector<OperatingPoint> & a = optimal_pts;
121 if (perf > a.back().perf) {
122 // keep unconditionally
123 a.push_back (op);
124 } else if (perf == a.back().perf) {
125 if (t < a.back ().t) {
126 a.back() = op;
127 } else {
128 return false;
129 }
130 } else {
131 int i;
132 // stricto sensu this should be a bissection
133 for (i = 0; i < a.size(); i++) {
134 if (a[i].perf >= perf) break;
135 }
136 assert (i < a.size());
137 if (t < a[i].t) {
138 if (a[i].perf == perf) {
139 a[i] = op;
140 } else {
141 a.insert (a.begin() + i, op);
142 }
143 } else {
144 return false;
145 }
146 }
147 { // remove non-optimal points from array
148 int i = a.size() - 1;
149 while (i > 0) {
150 if (a[i].t < a[i - 1].t)
151 a.erase (a.begin() + (i - 1));
152 i--;
153 }
154 }
155 return true;
156 }
157
158
159 int OperatingPoints::merge_with (const OperatingPoints &other,
160 const std::string & prefix)
161 {
162 int n_add = 0;
163 for (int i = 0; i < other.all_pts.size(); i++) {
164 const OperatingPoint & op = other.all_pts[i];
165 if (add (op.perf, op.t, prefix + op.key, op.cno))
166 n_add++;
167 }
168 return n_add;
169 }
170
171
172
173 /// get time required to obtain a given performance measure
174 double OperatingPoints::t_for_perf (double perf) const
175 {
176 const std::vector<OperatingPoint> & a = optimal_pts;
177 if (perf > a.back().perf) return 1e50;
178 int i0 = -1, i1 = a.size() - 1;
179 while (i0 + 1 < i1) {
180 int imed = (i0 + i1 + 1) / 2;
181 if (a[imed].perf < perf) i0 = imed;
182 else i1 = imed;
183 }
184 return a[i1].t;
185 }
186
187
188 void OperatingPoints::all_to_gnuplot (const char *fname) const
189 {
190 FILE *f = fopen(fname, "w");
191 if (!f) {
192 fprintf (stderr, "cannot open %s", fname);
193 perror("");
194 abort();
195 }
196 for (int i = 0; i < all_pts.size(); i++) {
197 const OperatingPoint & op = all_pts[i];
198 fprintf (f, "%g %g %s\n", op.perf, op.t, op.key.c_str());
199 }
200 fclose(f);
201 }
202
203 void OperatingPoints::optimal_to_gnuplot (const char *fname) const
204 {
205 FILE *f = fopen(fname, "w");
206 if (!f) {
207 fprintf (stderr, "cannot open %s", fname);
208 perror("");
209 abort();
210 }
211 double prev_perf = 0.0;
212 for (int i = 0; i < optimal_pts.size(); i++) {
213 const OperatingPoint & op = optimal_pts[i];
214 fprintf (f, "%g %g\n", prev_perf, op.t);
215 fprintf (f, "%g %g %s\n", op.perf, op.t, op.key.c_str());
216 prev_perf = op.perf;
217 }
218 fclose(f);
219 }
220
221 void OperatingPoints::display (bool only_optimal) const
222 {
223 const std::vector<OperatingPoint> &pts =
224 only_optimal ? optimal_pts : all_pts;
225 printf("Tested %ld operating points, %ld ones are optimal:\n",
226 all_pts.size(), optimal_pts.size());
227
228 for (int i = 0; i < pts.size(); i++) {
229 const OperatingPoint & op = pts[i];
230 const char *star = "";
231 if (!only_optimal) {
232 for (int j = 0; j < optimal_pts.size(); j++) {
233 if (op.cno == optimal_pts[j].cno) {
234 star = "*";
235 break;
236 }
237 }
238 }
239 printf ("cno=%ld key=%s perf=%.4f t=%.3f %s\n",
240 op.cno, op.key.c_str(), op.perf, op.t, star);
241 }
242
243 }
244
245 /***************************************************************
246 * ParameterSpace
247 ***************************************************************/
248
249 ParameterSpace::ParameterSpace ():
250 verbose (1), n_experiments (500),
251 batchsize (1<<30), thread_over_batches (false)
252 {
253 }
254
255 /* not keeping this constructor as inheritors will call the parent
256 initialize()
257 */
258
259 #if 0
260 ParameterSpace::ParameterSpace (Index *index):
261 verbose (1), n_experiments (500),
262 batchsize (1<<30), thread_over_batches (false)
263 {
264 initialize(index);
265 }
266 #endif
267
268 size_t ParameterSpace::n_combinations () const
269 {
270 size_t n = 1;
271 for (int i = 0; i < parameter_ranges.size(); i++)
272 n *= parameter_ranges[i].values.size();
273 return n;
274 }
275
276 /// get string representation of the combination
277 std::string ParameterSpace::combination_name (size_t cno) const {
278 char buf[1000], *wp = buf;
279 *wp = 0;
280 for (int i = 0; i < parameter_ranges.size(); i++) {
281 const ParameterRange & pr = parameter_ranges[i];
282 size_t j = cno % pr.values.size();
283 cno /= pr.values.size();
284 wp += snprintf (
285 wp, buf + 1000 - wp, "%s%s=%g", i == 0 ? "" : ",",
286 pr.name.c_str(), pr.values[j]);
287 }
288 return std::string (buf);
289 }
290
291
292 bool ParameterSpace::combination_ge (size_t c1, size_t c2) const
293 {
294 for (int i = 0; i < parameter_ranges.size(); i++) {
295 int nval = parameter_ranges[i].values.size();
296 size_t j1 = c1 % nval;
297 size_t j2 = c2 % nval;
298 if (!(j1 >= j2)) return false;
299 c1 /= nval;
300 c2 /= nval;
301 }
302 return true;
303 }
304
305
306
307 #define DC(classname) \
308 const classname *ix = dynamic_cast<const classname *>(index)
309
310 static void init_pq_ParameterRange (const ProductQuantizer & pq,
311 ParameterRange & pr)
312 {
313 if (pq.code_size % 4 == 0) {
314 // Polysemous not supported for code sizes that are not a
315 // multiple of 4
316 for (int i = 2; i <= pq.code_size * 8 / 2; i+= 2)
317 pr.values.push_back(i);
318 }
319 pr.values.push_back (pq.code_size * 8);
320 }
321
322 ParameterRange &ParameterSpace::add_range(const char * name)
323 {
324 parameter_ranges.push_back (ParameterRange ());
325 parameter_ranges.back ().name = name;
326 return parameter_ranges.back ();
327 }
328
329
330 /// initialize with reasonable parameters for the index
331 void ParameterSpace::initialize (const Index * index)
332 {
333 if (DC (IndexPreTransform)) {
334 index = ix->index;
335 }
336 if (DC (IndexRefineFlat)) {
337 ParameterRange & pr = add_range("k_factor_rf");
338 for (int i = 0; i <= 6; i++) {
339 pr.values.push_back (1 << i);
340 }
341 index = ix->base_index;
342 }
343 if (DC (IndexPreTransform)) {
344 index = ix->index;
345 }
346
347 if (DC (IndexIVF)) {
348 {
349 ParameterRange & pr = add_range("nprobe");
350 for (int i = 0; i < 13; i++) {
351 size_t nprobe = 1 << i;
352 if (nprobe >= ix->nlist) break;
353 pr.values.push_back (nprobe);
354 }
355 }
356 }
357 if (DC (IndexPQ)) {
358 ParameterRange & pr = add_range("ht");
359 init_pq_ParameterRange (ix->pq, pr);
360 }
361 if (DC (IndexIVFPQ)) {
362 ParameterRange & pr = add_range("ht");
363 init_pq_ParameterRange (ix->pq, pr);
364
365 const MultiIndexQuantizer *miq =
366 dynamic_cast<const MultiIndexQuantizer *> (ix->quantizer);
367 if (miq) {
368 ParameterRange & pr_max_codes = add_range("max_codes");
369 for (int i = 8; i < 20; i++) {
370 pr_max_codes.values.push_back (1 << i);
371 }
372 pr_max_codes.values.push_back (1.0 / 0.0);
373 }
374 }
375 if (DC (IndexIVFPQR)) {
376 ParameterRange & pr = add_range("k_factor");
377 for (int i = 0; i <= 6; i++) {
378 pr.values.push_back (1 << i);
379 }
380 }
381 }
382
383 #undef DC
384
385 // non-const version
386 #define DC(classname) classname *ix = dynamic_cast<classname *>(index)
387
388
389 /// set a combination of parameters on an index
390 void ParameterSpace::set_index_parameters (Index *index, size_t cno) const
391 {
392
393 for (int i = 0; i < parameter_ranges.size(); i++) {
394 const ParameterRange & pr = parameter_ranges[i];
395 size_t j = cno % pr.values.size();
396 cno /= pr.values.size();
397 double val = pr.values [j];
398 set_index_parameter (index, pr.name, val);
399 }
400 }
401
402 /// set a combination of parameters on an index
403 void ParameterSpace::set_index_parameters (
404 Index *index, const char *description_in) const
405 {
406 char description[strlen(description_in) + 1];
407 char *ptr;
408 memcpy (description, description_in, strlen(description_in) + 1);
409
410 for (char *tok = strtok_r (description, " ,", &ptr);
411 tok;
412 tok = strtok_r (nullptr, " ,", &ptr)) {
413 char name[100];
414 double val;
415 int ret = sscanf (tok, "%100[^=]=%lf", name, &val);
416 FAISS_THROW_IF_NOT_FMT (
417 ret == 2, "could not interpret parameters %s", tok);
418 set_index_parameter (index, name, val);
419 }
420
421 }
422
423 void ParameterSpace::set_index_parameter (
424 Index * index, const std::string & name, double val) const
425 {
426 if (verbose > 1)
427 printf(" set %s=%g\n", name.c_str(), val);
428
429 if (name == "verbose") {
430 index->verbose = int(val);
431 // and fall through to also enable it on sub-indexes
432 }
433 if (DC (IndexPreTransform)) {
434 index = ix->index;
435 }
436 if (DC (IndexShards)) {
437 // call on all sub-indexes
438 for (auto & shard_index : ix->shard_indexes) {
439 set_index_parameter (shard_index, name, val);
440 }
441 return;
442 }
443 if (name == "verbose") {
444 index->verbose = int(val);
445 // in case it was an IndexPreTransform
446 }
447 if (DC (IndexRefineFlat)) {
448 if (name == "k_factor_rf") {
449 ix->k_factor = int(val);
450 return;
451 }
452 index = ix->base_index;
453 }
454 if (DC (IndexPreTransform)) {
455 index = ix->index;
456 }
457 if (name == "verbose") {
458 index->verbose = int(val);
459 return; // last verbose that we could find
460 }
461 if (name == "nprobe") {
462 if ( DC(IndexIVF)) {
463 ix->nprobe = int(val);
464 return;
465 }
466 }
467 if (name == "ht") {
468 if (DC (IndexPQ)) {
469 if (val >= ix->pq.code_size * 8) {
470 ix->search_type = IndexPQ::ST_PQ;
471 } else {
472 ix->search_type = IndexPQ::ST_polysemous;
473 ix->polysemous_ht = int(val);
474 }
475 return;
476 } else if (DC (IndexIVFPQ)) {
477 if (val >= ix->pq.code_size * 8) {
478 ix->polysemous_ht = 0;
479 } else {
480 ix->polysemous_ht = int(val);
481 }
482 return;
483 }
484 }
485
486 if (name == "k_factor") {
487 if (DC (IndexIVFPQR)) {
488 ix->k_factor = val;
489 return;
490 }
491 }
492 if (name == "max_codes") {
493 if (DC (IndexIVFPQ)) {
494 ix->max_codes = finite(val) ? size_t(val) : 0;
495 return;
496 }
497 }
498 FAISS_THROW_FMT ("ParameterSpace::set_index_parameter:"
499 "could not set parameter %s",
500 name.c_str());
501 }
502
503 void ParameterSpace::display () const
504 {
505 printf ("ParameterSpace, %ld parameters, %ld combinations:\n",
506 parameter_ranges.size (), n_combinations ());
507 for (int i = 0; i < parameter_ranges.size(); i++) {
508 const ParameterRange & pr = parameter_ranges[i];
509 printf (" %s: ", pr.name.c_str ());
510 char sep = '[';
511 for (int j = 0; j < pr.values.size(); j++) {
512 printf ("%c %g", sep, pr.values [j]);
513 sep = ',';
514 }
515 printf ("]\n");
516 }
517 }
518
519
520
521 void ParameterSpace::update_bounds (size_t cno, const OperatingPoint & op,
522 double *upper_bound_perf,
523 double *lower_bound_t) const
524 {
525 if (combination_ge (cno, op.cno)) {
526 if (op.t > *lower_bound_t) *lower_bound_t = op.t;
527 }
528 if (combination_ge (op.cno, cno)) {
529 if (op.perf < *upper_bound_perf) *upper_bound_perf = op.perf;
530 }
531 }
532
533
534
535 void ParameterSpace::explore (Index *index,
536 size_t nq, const float *xq,
537 const AutoTuneCriterion & crit,
538 OperatingPoints * ops) const
539 {
540 FAISS_THROW_IF_NOT_MSG (nq == crit.nq,
541 "criterion does not have the same nb of queries");
542
543 size_t n_comb = n_combinations ();
544
545 if (n_experiments == 0) {
546
547 for (size_t cno = 0; cno < n_comb; cno++) {
548 set_index_parameters (index, cno);
549 std::vector<Index::idx_t> I(nq * crit.nnn);
550 std::vector<float> D(nq * crit.nnn);
551
552 double t0 = getmillisecs ();
553 index->search (nq, xq, crit.nnn, D.data(), I.data());
554 double t_search = (getmillisecs() - t0) / 1e3;
555
556 double perf = crit.evaluate (D.data(), I.data());
557
558 bool keep = ops->add (perf, t_search, combination_name (cno), cno);
559
560 if (verbose)
561 printf(" %ld/%ld: %s perf=%.3f t=%.3f s %s\n", cno, n_comb,
562 combination_name (cno).c_str(), perf, t_search,
563 keep ? "*" : "");
564 }
565 return;
566 }
567
568 int n_exp = n_experiments;
569
570 if (n_exp > n_comb) n_exp = n_comb;
571 FAISS_THROW_IF_NOT (n_comb == 1 || n_exp > 2);
572 std::vector<int> perm (n_comb);
573 // make sure the slowest and fastest experiment are run
574 perm[0] = 0;
575 if (n_comb > 1) {
576 perm[1] = n_comb - 1;
577 rand_perm (&perm[2], n_comb - 2, 1234);
578 for (int i = 2; i < perm.size(); i++) perm[i] ++;
579 }
580
581 for (size_t xp = 0; xp < n_exp; xp++) {
582 size_t cno = perm[xp];
583
584 if (verbose)
585 printf(" %ld/%d: cno=%ld %s ", xp, n_exp, cno,
586 combination_name (cno).c_str());
587
588 {
589 double lower_bound_t = 0.0;
590 double upper_bound_perf = 1.0;
591 for (int i = 0; i < ops->all_pts.size(); i++) {
592 update_bounds (cno, ops->all_pts[i],
593 &upper_bound_perf, &lower_bound_t);
594 }
595 double best_t = ops->t_for_perf (upper_bound_perf);
596 if (verbose)
597 printf ("bounds [perf<=%.3f t>=%.3f] %s",
598 upper_bound_perf, lower_bound_t,
599 best_t <= lower_bound_t ? "skip\n" : "");
600 if (best_t <= lower_bound_t) continue;
601 }
602
603 set_index_parameters (index, cno);
604 std::vector<Index::idx_t> I(nq * crit.nnn);
605 std::vector<float> D(nq * crit.nnn);
606
607 double t0 = getmillisecs ();
608
609 if (thread_over_batches) {
610 #pragma omp parallel for
611 for (size_t q0 = 0; q0 < nq; q0 += batchsize) {
612 size_t q1 = q0 + batchsize;
613 if (q1 > nq) q1 = nq;
614 index->search (q1 - q0, xq + q0 * index->d,
615 crit.nnn,
616 D.data() + q0 * crit.nnn,
617 I.data() + q0 * crit.nnn);
618 }
619 } else {
620 for (size_t q0 = 0; q0 < nq; q0 += batchsize) {
621 size_t q1 = q0 + batchsize;
622 if (q1 > nq) q1 = nq;
623 index->search (q1 - q0, xq + q0 * index->d,
624 crit.nnn,
625 D.data() + q0 * crit.nnn,
626 I.data() + q0 * crit.nnn);
627 }
628 }
629
630 double t_search = (getmillisecs() - t0) / 1e3;
631
632 double perf = crit.evaluate (D.data(), I.data());
633
634 bool keep = ops->add (perf, t_search, combination_name (cno), cno);
635
636 if (verbose)
637 printf(" perf %.3f t %.3f %s\n", perf, t_search,
638 keep ? "*" : "");
639 }
640 }
641
642 /***************************************************************
643 * index_factory
644 ***************************************************************/
645
646 namespace {
647
648 struct VTChain {
649 std::vector<VectorTransform *> chain;
650 ~VTChain () {
651 for (int i = 0; i < chain.size(); i++) {
652 delete chain[i];
653 }
654 }
655 };
656
657
658 /// what kind of training does this coarse quantizer require?
659 char get_trains_alone(const Index *coarse_quantizer) {
660 return
661 dynamic_cast<const MultiIndexQuantizer*>(coarse_quantizer) ? 1 :
662 0;
663 }
664
665
666 }
667
668 Index *index_factory (int d, const char *description_in, MetricType metric)
669 {
670 VTChain vts;
671 Index *coarse_quantizer = nullptr;
672 Index *index = nullptr;
673 bool add_idmap = false;
674 bool make_IndexRefineFlat = false;
675
676 ScopeDeleter1<Index> del_coarse_quantizer, del_index;
677
678 char description[strlen(description_in) + 1];
679 char *ptr;
680 memcpy (description, description_in, strlen(description_in) + 1);
681
682 int ncentroids = -1;
683
684 for (char *tok = strtok_r (description, " ,", &ptr);
685 tok;
686 tok = strtok_r (nullptr, " ,", &ptr)) {
687 int d_out, opq_M, nbit, M, M2;
688 char option[100];
689 std::string stok(tok);
690
691 // to avoid mem leaks with exceptions:
692 // do all tests before any instanciation
693
694 VectorTransform *vt_1 = nullptr;
695 Index *coarse_quantizer_1 = nullptr;
696 Index *index_1 = nullptr;
697
698 // VectorTransforms
699 if (sscanf (tok, "PCA%d", &d_out) == 1) {
700 vt_1 = new PCAMatrix (d, d_out);
701 d = d_out;
702 } else if (sscanf (tok, "PCAR%d", &d_out) == 1) {
703 vt_1 = new PCAMatrix (d, d_out, 0, true);
704 d = d_out;
705 } else if (sscanf (tok, "PCAW%d", &d_out) == 1) {
706 vt_1 = new PCAMatrix (d, d_out, -0.5, false);
707 d = d_out;
708 } else if (sscanf (tok, "PCAWR%d", &d_out) == 1) {
709 vt_1 = new PCAMatrix (d, d_out, -0.5, true);
710 d = d_out;
711 } else if (sscanf (tok, "OPQ%d_%d", &opq_M, &d_out) == 2) {
712 vt_1 = new OPQMatrix (d, opq_M, d_out);
713 d = d_out;
714 } else if (sscanf (tok, "OPQ%d", &opq_M) == 1) {
715 vt_1 = new OPQMatrix (d, opq_M);
716 } else if (stok == "L2norm") {
717 vt_1 = new NormalizationTransform (d, 2.0);
718
719
720 } else if (!coarse_quantizer &&
721 sscanf (tok, "IVF%d", &ncentroids) == 1) {
722 if (metric == METRIC_L2) {
723 coarse_quantizer_1 = new IndexFlatL2 (d);
724 } else { // if (metric == METRIC_IP)
725 coarse_quantizer_1 = new IndexFlatIP (d);
726 }
727 } else if (!coarse_quantizer && sscanf (tok, "IMI2x%d", &nbit) == 1) {
728 FAISS_THROW_IF_NOT_MSG (metric == METRIC_L2,
729 "MultiIndex not implemented for inner prod search");
730 coarse_quantizer_1 = new MultiIndexQuantizer (d, 2, nbit);
731 ncentroids = 1 << (2 * nbit);
732 } else if (stok == "IDMap") {
733 add_idmap = true;
734
735 // IVFs
736 } else if (!index && stok == "Flat") {
737 if (coarse_quantizer) {
738 // if there was an IVF in front, then it is an IVFFlat
739 IndexIVF *index_ivf = new IndexIVFFlat (
740 coarse_quantizer, d, ncentroids, metric);
741 index_ivf->quantizer_trains_alone =
742 get_trains_alone (coarse_quantizer);
743 index_ivf->cp.spherical = metric == METRIC_INNER_PRODUCT;
744 del_coarse_quantizer.release ();
745 index_ivf->own_fields = true;
746 index_1 = index_ivf;
747 } else {
748 index_1 = new IndexFlat (d, metric);
749 }
750 } else if (!index && (stok == "SQ8" || stok == "SQ4")) {
751 ScalarQuantizer::QuantizerType qt =
752 stok == "SQ8" ? ScalarQuantizer::QT_8bit :
753 stok == "SQ4" ? ScalarQuantizer::QT_4bit :
754 ScalarQuantizer::QT_4bit;
755 if (coarse_quantizer) {
756 IndexIVFScalarQuantizer *index_ivf =
757 new IndexIVFScalarQuantizer (
758 coarse_quantizer, d, ncentroids, qt, metric);
759 index_ivf->quantizer_trains_alone =
760 get_trains_alone (coarse_quantizer);
761 del_coarse_quantizer.release ();
762 index_ivf->own_fields = true;
763 index_1 = index_ivf;
764 } else {
765 index_1 = new IndexScalarQuantizer (d, qt, metric);
766 }
767 } else if (!index && sscanf (tok, "PQ%d+%d", &M, &M2) == 2) {
768 FAISS_THROW_IF_NOT_MSG(coarse_quantizer,
769 "PQ with + works only with an IVF");
770 FAISS_THROW_IF_NOT_MSG(metric == METRIC_L2,
771 "IVFPQR not implemented for inner product search");
772 IndexIVFPQR *index_ivf = new IndexIVFPQR (
773 coarse_quantizer, d, ncentroids, M, 8, M2, 8);
774 index_ivf->quantizer_trains_alone =
775 get_trains_alone (coarse_quantizer);
776 del_coarse_quantizer.release ();
777 index_ivf->own_fields = true;
778 index_1 = index_ivf;
779 } else if (!index && sscanf (tok, "PQ%d%10s", &M, option) == 2) {
780 std::string soption = option;
781 // np to disable polysemous trainign
782 FAISS_THROW_IF_NOT(soption == "" || soption == "np");
783 if (coarse_quantizer) {
784 IndexIVFPQ *index_ivf = new IndexIVFPQ (
785 coarse_quantizer, d, ncentroids, M, 8);
786 index_ivf->quantizer_trains_alone =
787 get_trains_alone (coarse_quantizer);
788 index_ivf->metric_type = metric;
789 index_ivf->cp.spherical = metric == METRIC_INNER_PRODUCT;
790 del_coarse_quantizer.release ();
791 index_ivf->own_fields = true;
792 index_ivf->do_polysemous_training = soption != "np";
793 index_1 = index_ivf;
794 } else {
795 IndexPQ *index_pq = new IndexPQ (d, M, 8, metric);
796 index_pq->do_polysemous_training = soption != "np";
797 index_1 = index_pq;
798 }
799
800 } else if (stok == "RFlat") {
801 make_IndexRefineFlat = true;
802 } else {
803 FAISS_THROW_FMT( "could not parse token \"%s\" in %s\n",
804 tok, description_in);
805 }
806
807 if (index_1 && add_idmap) {
808 IndexIDMap *idmap = new IndexIDMap(index_1);
809 del_index.set (idmap);
810 idmap->own_fields = true;
811 index_1 = idmap;
812 add_idmap = false;
813 }
814
815 if (vt_1) {
816 vts.chain.push_back (vt_1);
817 }
818
819 if (coarse_quantizer_1) {
820 coarse_quantizer = coarse_quantizer_1;
821 del_coarse_quantizer.set (coarse_quantizer);
822 }
823
824 if (index_1) {
825 index = index_1;
826 del_index.set (index);
827 }
828 }
829
830 FAISS_THROW_IF_NOT_FMT(index, "descrption %s did not generate an index",
831 description_in);
832
833 // nothing can go wrong now
834 del_index.release ();
835 del_coarse_quantizer.release ();
836
837 if (add_idmap) {
838 fprintf(stderr, "index_factory: WARNING: "
839 "IDMap option not used\n");
840 }
841
842 if (vts.chain.size() > 0) {
843 IndexPreTransform *index_pt = new IndexPreTransform (index);
844 index_pt->own_fields = true;
845 // add from back
846 while (vts.chain.size() > 0) {
847 index_pt->prepend_transform (vts.chain.back());
848 vts.chain.pop_back ();
849 }
850 index = index_pt;
851 }
852
853 if (make_IndexRefineFlat) {
854 IndexRefineFlat *index_rf = new IndexRefineFlat (index);
855 index_rf->own_fields = true;
856 index = index_rf;
857 }
858
859 return index;
860 }
861
862
863
864
865 }; // namespace faiss
faiss::ParameterSpace::explore
void explore(Index *index, size_t nq, const float *xq, const AutoTuneCriterion &crit, OperatingPoints *ops) const
Definition: AutoTune.cpp:535
faiss::IndexIVF
Definition: IndexIVF.h:45
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Definition: AutoTune.h:134
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Definition: AutoTune.h:89
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Definition: IndexScalarQuantizer.h:32
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Definition: IndexFlat.h:23
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Definition: AutoTune.h:90
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Definition: IndexIVFPQ.h:168
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Definition: IndexPQ.h:69
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Definition: IndexScalarQuantizer.h:82
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Definition: IndexIVF.h:56
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Definition: AutoTune.cpp:221
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Definition: IndexPQ.h:28
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Definition: AutoTune.h:87
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Definition: IndexScalarQuantizer.h:34
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Definition: AutoTune.h:93
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Definition: AutoTune.cpp:174
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Definition: AutoTune.h:29
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Definition: IndexFlat.h:79
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Definition: VectorTransform.h:180
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Definition: FaissException.h:52
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Definition: IndexIVFPQ.h:34
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Definition: AutoTune.h:145
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Definition: VectorTransform.h:239
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Definition: MetaIndexes.h:26
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Definition: AutoTune.h:28
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Definition: IndexIVF.h:181
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Definition: AutoTune.h:98
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Definition: IndexFlat.h:73
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Definition: AutoTune.cpp:36
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Definition: AutoTune.cpp:322
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Definition: IndexFlat.h:103
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Definition: AutoTune.h:30
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output to a format easy to digest by gnuplot
Definition: AutoTune.cpp:188
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should the base index be deallocated?
Definition: IndexFlat.h:110
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int d
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Definition: Index.h:64
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size_t code_size
byte per indexed vector
Definition: ProductQuantizer.h:34
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Definition: IndexIVFPQ.h:29
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ClusteringParameters cp
to override default clustering params
Definition: IndexIVF.h:59
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bool thread_over_batches
Definition: AutoTune.h:149
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Definition: IndexIVF.h:57
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Definition: AutoTune.h:95
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size_t ranklist_intersection_size(size_t k1, const long *v1, size_t k2, const long *v2_in)
Definition: utils.cpp:1574
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Definition: AutoTune.h:26
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Definition: Index.h:66
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double getmillisecs()
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Definition: utils.cpp:74
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Definition: AutoTune.h:32
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Definition: IndexScalarQuantizer.h:129
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Definition: AutoTune.cpp:277
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Definition: IndexPQ.h:135
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Definition: VectorTransform.h:28
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Definition: VectorTransform.h:244
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Definition: AutoTune.cpp:331
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int verbose
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Definition: AutoTune.h:139
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int merge_with(const OperatingPoints &other, const std::string &prefix="")
add operating points from other to this, with a prefix to the keys
Definition: AutoTune.cpp:159
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virtual void set_index_parameter(Index *index, const std::string &name, double val) const
set one of the parameters
Definition: AutoTune.cpp:423
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Definition: AutoTune.cpp:268
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Definition: Index.h:72
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Definition: AutoTune.cpp:390
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Definition: IndexScalarQuantizer.h:33
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Definition: Index.h:60
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Definition: IndexPQ.h:76
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Definition: AutoTune.cpp:503
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Definition: IndexPQ.h:80
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Definition: MetaIndexes.h:86
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Definition: ProductQuantizer.h:25
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Definition: Clustering.h:29
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Definition: AutoTune.h:125
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Definition: AutoTune.cpp:668
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Definition: AutoTune.h:142
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