-
Notifications
You must be signed in to change notification settings - Fork 1
/
opendataval.dataval.lava.html
772 lines (726 loc) · 70.8 KB
/
opendataval.dataval.lava.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
<!doctype html>
<html class="no-js" lang="en" data-content_root="./">
<head><meta charset="utf-8"/>
<meta name="viewport" content="width=device-width,initial-scale=1"/>
<meta name="color-scheme" content="light dark"><meta name="viewport" content="width=device-width, initial-scale=1" />
<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="opendataval.dataval.margcontrib package" href="opendataval.dataval.margcontrib.html" /><link rel="prev" title="opendataval.dataval.knnshap package" href="opendataval.dataval.knnshap.html" />
<link rel="shortcut icon" href="_static/favicon.ico"/><!-- Generated with Sphinx 7.2.6 and Furo 2023.09.10 -->
<title>opendataval.dataval.lava package - OpenDataVal documentation</title>
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=a746c00c" />
<link rel="stylesheet" type="text/css" href="_static/styles/furo.css?v=135e06be" />
<link rel="stylesheet" type="text/css" href="_static/styles/furo-extensions.css?v=36a5483c" />
<style>
body {
--color-code-background: #f8f8f8;
--color-code-foreground: black;
}
@media not print {
body[data-theme="dark"] {
--color-code-background: #202020;
--color-code-foreground: #d0d0d0;
}
@media (prefers-color-scheme: dark) {
body:not([data-theme="light"]) {
--color-code-background: #202020;
--color-code-foreground: #d0d0d0;
}
}
}
</style></head>
<body>
<script>
document.body.dataset.theme = localStorage.getItem("theme") || "auto";
</script>
<svg xmlns="http://www.w3.org/2000/svg" style="display: none;">
<symbol id="svg-toc" viewBox="0 0 24 24">
<title>Contents</title>
<svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 1024 1024">
<path d="M408 442h480c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8H408c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8zm-8 204c0 4.4 3.6 8 8 8h480c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8H408c-4.4 0-8 3.6-8 8v56zm504-486H120c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8h784c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8zm0 632H120c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8h784c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8zM115.4 518.9L271.7 642c5.8 4.6 14.4.5 14.4-6.9V388.9c0-7.4-8.5-11.5-14.4-6.9L115.4 505.1a8.74 8.74 0 0 0 0 13.8z"/>
</svg>
</symbol>
<symbol id="svg-menu" viewBox="0 0 24 24">
<title>Menu</title>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor"
stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="feather-menu">
<line x1="3" y1="12" x2="21" y2="12"></line>
<line x1="3" y1="6" x2="21" y2="6"></line>
<line x1="3" y1="18" x2="21" y2="18"></line>
</svg>
</symbol>
<symbol id="svg-arrow-right" viewBox="0 0 24 24">
<title>Expand</title>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor"
stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="feather-chevron-right">
<polyline points="9 18 15 12 9 6"></polyline>
</svg>
</symbol>
<symbol id="svg-sun" viewBox="0 0 24 24">
<title>Light mode</title>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" class="feather-sun">
<circle cx="12" cy="12" r="5"></circle>
<line x1="12" y1="1" x2="12" y2="3"></line>
<line x1="12" y1="21" x2="12" y2="23"></line>
<line x1="4.22" y1="4.22" x2="5.64" y2="5.64"></line>
<line x1="18.36" y1="18.36" x2="19.78" y2="19.78"></line>
<line x1="1" y1="12" x2="3" y2="12"></line>
<line x1="21" y1="12" x2="23" y2="12"></line>
<line x1="4.22" y1="19.78" x2="5.64" y2="18.36"></line>
<line x1="18.36" y1="5.64" x2="19.78" y2="4.22"></line>
</svg>
</symbol>
<symbol id="svg-moon" viewBox="0 0 24 24">
<title>Dark mode</title>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" class="icon-tabler-moon">
<path stroke="none" d="M0 0h24v24H0z" fill="none" />
<path d="M12 3c.132 0 .263 0 .393 0a7.5 7.5 0 0 0 7.92 12.446a9 9 0 1 1 -8.313 -12.454z" />
</svg>
</symbol>
<symbol id="svg-sun-half" viewBox="0 0 24 24">
<title>Auto light/dark mode</title>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" class="icon-tabler-shadow">
<path stroke="none" d="M0 0h24v24H0z" fill="none"/>
<circle cx="12" cy="12" r="9" />
<path d="M13 12h5" />
<path d="M13 15h4" />
<path d="M13 18h1" />
<path d="M13 9h4" />
<path d="M13 6h1" />
</svg>
</symbol>
</svg>
<input type="checkbox" class="sidebar-toggle" name="__navigation" id="__navigation">
<input type="checkbox" class="sidebar-toggle" name="__toc" id="__toc">
<label class="overlay sidebar-overlay" for="__navigation">
<div class="visually-hidden">Hide navigation sidebar</div>
</label>
<label class="overlay toc-overlay" for="__toc">
<div class="visually-hidden">Hide table of contents sidebar</div>
</label>
<div class="page">
<header class="mobile-header">
<div class="header-left">
<label class="nav-overlay-icon" for="__navigation">
<div class="visually-hidden">Toggle site navigation sidebar</div>
<i class="icon"><svg><use href="#svg-menu"></use></svg></i>
</label>
</div>
<div class="header-center">
<a href="index.html"><div class="brand">OpenDataVal documentation</div></a>
</div>
<div class="header-right">
<div class="theme-toggle-container theme-toggle-header">
<button class="theme-toggle">
<div class="visually-hidden">Toggle Light / Dark / Auto color theme</div>
<svg class="theme-icon-when-auto"><use href="#svg-sun-half"></use></svg>
<svg class="theme-icon-when-dark"><use href="#svg-moon"></use></svg>
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
<label class="toc-overlay-icon toc-header-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
</label>
</div>
</header>
<aside class="sidebar-drawer">
<div class="sidebar-container">
<div class="sidebar-sticky"><a class="sidebar-brand" href="index.html">
<div class="sidebar-logo-container">
<img class="sidebar-logo only-light" src="_static/logo-light-mode.png" alt="Light Logo"/>
<img class="sidebar-logo only-dark" src="_static/logo-dark-mode.png" alt="Dark Logo"/>
</div>
<span class="sidebar-brand-text">OpenDataVal documentation</span>
</a><form class="sidebar-search-container" method="get" action="search.html" role="search">
<input class="sidebar-search" placeholder="Search" name="q" aria-label="Search">
<input type="hidden" name="check_keywords" value="yes">
<input type="hidden" name="area" value="default">
</form>
<div id="searchbox"></div><div class="sidebar-scroll"><div class="sidebar-tree">
<ul class="current">
<li class="toctree-l1 current has-children"><a class="reference internal" href="modules.html">modules</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" role="switch" type="checkbox"/><label for="toctree-checkbox-1"><div class="visually-hidden">Toggle navigation of modules</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul class="current">
<li class="toctree-l2 current has-children"><a class="reference internal" href="opendataval.html">opendataval package</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-2" name="toctree-checkbox-2" role="switch" type="checkbox"/><label for="toctree-checkbox-2"><div class="visually-hidden">Toggle navigation of opendataval package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul class="current">
<li class="toctree-l3 has-children"><a class="reference internal" href="opendataval.dataloader.html">opendataval.dataloader package</a><input class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" role="switch" type="checkbox"/><label for="toctree-checkbox-3"><div class="visually-hidden">Toggle navigation of opendataval.dataloader package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4 has-children"><a class="reference internal" href="opendataval.dataloader.datasets.html">opendataval.dataloader.datasets package</a><input class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" role="switch" type="checkbox"/><label for="toctree-checkbox-4"><div class="visually-hidden">Toggle navigation of opendataval.dataloader.datasets package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l5"><a class="reference internal" href="generated/opendataval.dataloader.datasets.datasets.html">opendataval.dataloader.datasets.datasets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/opendataval.dataloader.datasets.imagesets.html">opendataval.dataloader.datasets.imagesets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/opendataval.dataloader.datasets.nlpsets.html">opendataval.dataloader.datasets.nlpsets</a></li>
</ul>
</li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.Register.html">opendataval.dataloader.Register</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.DataFetcher.html">opendataval.dataloader.DataFetcher</a></li>
<li class="toctree-l4 has-children"><a class="reference internal" href="generated/opendataval.dataloader.datasets.html">opendataval.dataloader.datasets</a><input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" role="switch" type="checkbox"/><label for="toctree-checkbox-5"><div class="visually-hidden">Toggle navigation of opendataval.dataloader.datasets</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/opendataval.dataloader.datasets.datasets.html">opendataval.dataloader.datasets.datasets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/opendataval.dataloader.datasets.imagesets.html">opendataval.dataloader.datasets.imagesets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/opendataval.dataloader.datasets.nlpsets.html">opendataval.dataloader.datasets.nlpsets</a></li>
</ul>
</li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.cache.html">opendataval.dataloader.cache</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.mix_labels.html">opendataval.dataloader.mix_labels</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.one_hot_encode.html">opendataval.dataloader.one_hot_encode</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataloader.CatDataset.html">opendataval.dataloader.CatDataset</a></li>
</ul>
</li>
<li class="toctree-l3 current has-children"><a class="reference internal" href="opendataval.dataval.html">opendataval.dataval package</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" role="switch" type="checkbox"/><label for="toctree-checkbox-6"><div class="visually-hidden">Toggle navigation of opendataval.dataval package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul class="current">
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.ame.html">opendataval.dataval.ame package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.csshap.html">opendataval.dataval.csshap package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.dvrl.html">opendataval.dataval.dvrl package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.influence.html">opendataval.dataval.influence package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.knnshap.html">opendataval.dataval.knnshap package</a></li>
<li class="toctree-l4 current current-page"><a class="current reference internal" href="#">opendataval.dataval.lava package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.margcontrib.html">opendataval.dataval.margcontrib package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.oob.html">opendataval.dataval.oob package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.random.html">opendataval.dataval.random package</a></li>
<li class="toctree-l4"><a class="reference internal" href="opendataval.dataval.volume.html">opendataval.dataval.volume package</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.DataEvaluator.html">opendataval.dataval.DataEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.ModelMixin.html">opendataval.dataval.ModelMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.ModelLessMixin.html">opendataval.dataval.ModelLessMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.AME.html">opendataval.dataval.AME</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.DVRL.html">opendataval.dataval.DVRL</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.InfluenceFunction.html">opendataval.dataval.InfluenceFunction</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.InfluenceSubsample.html">opendataval.dataval.InfluenceSubsample</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.KNNShapley.html">opendataval.dataval.KNNShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.DataOob.html">opendataval.dataval.DataOob</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.DataBanzhaf.html">opendataval.dataval.DataBanzhaf</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.BetaShapley.html">opendataval.dataval.BetaShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.DataShapley.html">opendataval.dataval.DataShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.LavaEvaluator.html">opendataval.dataval.LavaEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.LeaveOneOut.html">opendataval.dataval.LeaveOneOut</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.ShapEvaluator.html">opendataval.dataval.ShapEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.RandomEvaluator.html">opendataval.dataval.RandomEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.RobustVolumeShapley.html">opendataval.dataval.RobustVolumeShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.Sampler.html">opendataval.dataval.Sampler</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.TMCSampler.html">opendataval.dataval.TMCSampler</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.dataval.GrTMCSampler.html">opendataval.dataval.GrTMCSampler</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="opendataval.experiment.html">opendataval.experiment package</a><input class="toctree-checkbox" id="toctree-checkbox-7" name="toctree-checkbox-7" role="switch" type="checkbox"/><label for="toctree-checkbox-7"><div class="visually-hidden">Toggle navigation of opendataval.experiment package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.experiment.ExperimentMediator.html">opendataval.experiment.ExperimentMediator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.experiment.exper_methods.html">opendataval.experiment.exper_methods</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="opendataval.model.html">opendataval.model package</a><input class="toctree-checkbox" id="toctree-checkbox-8" name="toctree-checkbox-8" role="switch" type="checkbox"/><label for="toctree-checkbox-8"><div class="visually-hidden">Toggle navigation of opendataval.model package</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.Model.html">opendataval.model.Model</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.GradientModel.html">opendataval.model.GradientModel</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.ModelFactory.html">opendataval.model.ModelFactory</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.TorchClassMixin.html">opendataval.model.TorchClassMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.TorchRegressMixin.html">opendataval.model.TorchRegressMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.TorchPredictMixin.html">opendataval.model.TorchPredictMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.TorchGradMixin.html">opendataval.model.TorchGradMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.ClassifierSkLearnWrapper.html">opendataval.model.ClassifierSkLearnWrapper</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.ClassifierUnweightedSkLearnWrapper.html">opendataval.model.ClassifierUnweightedSkLearnWrapper</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/opendataval.model.RegressionSkLearnWrapper.html">opendataval.model.RegressionSkLearnWrapper</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="generated/opendataval.dataloader.html">opendataval.dataloader</a><input class="toctree-checkbox" id="toctree-checkbox-9" name="toctree-checkbox-9" role="switch" type="checkbox"/><label for="toctree-checkbox-9"><div class="visually-hidden">Toggle navigation of opendataval.dataloader</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.Register.html">opendataval.dataloader.Register</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.DataFetcher.html">opendataval.dataloader.DataFetcher</a></li>
<li class="toctree-l4 has-children"><a class="reference internal" href="generated/generated/opendataval.dataloader.datasets.html">opendataval.dataloader.datasets</a><input class="toctree-checkbox" id="toctree-checkbox-10" name="toctree-checkbox-10" role="switch" type="checkbox"/><label for="toctree-checkbox-10"><div class="visually-hidden">Toggle navigation of opendataval.dataloader.datasets</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/generated/opendataval.dataloader.datasets.datasets.html">opendataval.dataloader.datasets.datasets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/generated/opendataval.dataloader.datasets.imagesets.html">opendataval.dataloader.datasets.imagesets</a></li>
<li class="toctree-l5"><a class="reference internal" href="generated/generated/generated/opendataval.dataloader.datasets.nlpsets.html">opendataval.dataloader.datasets.nlpsets</a></li>
</ul>
</li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.cache.html">opendataval.dataloader.cache</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.mix_labels.html">opendataval.dataloader.mix_labels</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.one_hot_encode.html">opendataval.dataloader.one_hot_encode</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataloader.CatDataset.html">opendataval.dataloader.CatDataset</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="generated/opendataval.dataval.html">opendataval.dataval</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" role="switch" type="checkbox"/><label for="toctree-checkbox-11"><div class="visually-hidden">Toggle navigation of opendataval.dataval</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.DataEvaluator.html">opendataval.dataval.DataEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.ModelMixin.html">opendataval.dataval.ModelMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.ModelLessMixin.html">opendataval.dataval.ModelLessMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.AME.html">opendataval.dataval.AME</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.DVRL.html">opendataval.dataval.DVRL</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.InfluenceFunction.html">opendataval.dataval.InfluenceFunction</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.InfluenceSubsample.html">opendataval.dataval.InfluenceSubsample</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.KNNShapley.html">opendataval.dataval.KNNShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.DataOob.html">opendataval.dataval.DataOob</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.DataBanzhaf.html">opendataval.dataval.DataBanzhaf</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.BetaShapley.html">opendataval.dataval.BetaShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.DataShapley.html">opendataval.dataval.DataShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.LavaEvaluator.html">opendataval.dataval.LavaEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.LeaveOneOut.html">opendataval.dataval.LeaveOneOut</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.ShapEvaluator.html">opendataval.dataval.ShapEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.RandomEvaluator.html">opendataval.dataval.RandomEvaluator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.RobustVolumeShapley.html">opendataval.dataval.RobustVolumeShapley</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.Sampler.html">opendataval.dataval.Sampler</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.TMCSampler.html">opendataval.dataval.TMCSampler</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.dataval.GrTMCSampler.html">opendataval.dataval.GrTMCSampler</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="generated/opendataval.model.html">opendataval.model</a><input class="toctree-checkbox" id="toctree-checkbox-12" name="toctree-checkbox-12" role="switch" type="checkbox"/><label for="toctree-checkbox-12"><div class="visually-hidden">Toggle navigation of opendataval.model</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.Model.html">opendataval.model.Model</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.GradientModel.html">opendataval.model.GradientModel</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.ModelFactory.html">opendataval.model.ModelFactory</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.TorchClassMixin.html">opendataval.model.TorchClassMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.TorchRegressMixin.html">opendataval.model.TorchRegressMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.TorchPredictMixin.html">opendataval.model.TorchPredictMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.TorchGradMixin.html">opendataval.model.TorchGradMixin</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.ClassifierSkLearnWrapper.html">opendataval.model.ClassifierSkLearnWrapper</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.ClassifierUnweightedSkLearnWrapper.html">opendataval.model.ClassifierUnweightedSkLearnWrapper</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.model.RegressionSkLearnWrapper.html">opendataval.model.RegressionSkLearnWrapper</a></li>
</ul>
</li>
<li class="toctree-l3 has-children"><a class="reference internal" href="generated/opendataval.experiment.html">opendataval.experiment</a><input class="toctree-checkbox" id="toctree-checkbox-13" name="toctree-checkbox-13" role="switch" type="checkbox"/><label for="toctree-checkbox-13"><div class="visually-hidden">Toggle navigation of opendataval.experiment</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.experiment.ExperimentMediator.html">opendataval.experiment.ExperimentMediator</a></li>
<li class="toctree-l4"><a class="reference internal" href="generated/generated/opendataval.experiment.exper_methods.html">opendataval.experiment.exper_methods</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="generated/opendataval.util.set_random_state.html">opendataval.util.set_random_state</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/opendataval.util.load_mediator_output.html">opendataval.util.load_mediator_output</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/opendataval.__version__.html">opendataval.__version__</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="leaderboards.html">leaderboards</a></li>
<li class="toctree-l1"><a class="reference internal" href="license.html">license</a></li>
<li class="toctree-l1"><a class="reference internal" href="paper.html">paper</a></li>
</ul>
</div>
</div>
</div>
</div>
</aside>
<div class="main">
<div class="content">
<div class="article-container">
<a href="#" class="back-to-top muted-link">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24">
<path d="M13 20h-2V8l-5.5 5.5-1.42-1.42L12 4.16l7.92 7.92-1.42 1.42L13 8v12z"></path>
</svg>
<span>Back to top</span>
</a>
<div class="content-icon-container">
<div class="theme-toggle-container theme-toggle-content">
<button class="theme-toggle">
<div class="visually-hidden">Toggle Light / Dark / Auto color theme</div>
<svg class="theme-icon-when-auto"><use href="#svg-sun-half"></use></svg>
<svg class="theme-icon-when-dark"><use href="#svg-moon"></use></svg>
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
<label class="toc-overlay-icon toc-content-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
</label>
</div>
<article role="main">
<section id="opendataval-dataval-lava-package">
<h1>opendataval.dataval.lava package<a class="headerlink" href="#opendataval-dataval-lava-package" title="Link to this heading">#</a></h1>
<section id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading">#</a></h2>
</section>
<section id="module-opendataval.dataval.lava.lava">
<span id="opendataval-dataval-lava-lava-module"></span><h2>opendataval.dataval.lava.lava module<a class="headerlink" href="#module-opendataval.dataval.lava.lava" title="Link to this heading">#</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="opendataval.dataval.lava.lava.LavaEvaluator">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.lava.</span></span><span class="sig-name descname"><span class="pre">LavaEvaluator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.lava.LavaEvaluator" title="Link to this definition">#</a></dt>
<dd><p>Bases: <a class="reference internal" href="opendataval.dataval.html#opendataval.dataval.api.DataEvaluator" title="opendataval.dataval.api.DataEvaluator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataEvaluator</span></code></a>, <a class="reference internal" href="opendataval.dataval.html#opendataval.dataval.api.ModelLessMixin" title="opendataval.dataval.api.ModelLessMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelLessMixin</span></code></a></p>
<p>Data valuation using LAVA implementation.</p>
<section id="references">
<h3>References<a class="headerlink" href="#references" title="Link to this heading">#</a></h3>
<aside class="footnote-list brackets">
<aside class="footnote brackets" id="id1" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
<p>H. A. Just, F. Kang, T. Wang, Y. Zeng, M. Ko, M. Jin, and R. Jia,
LAVA: Data Valuation without Pre-Specified Learning Algorithms,
2023. Available: <a class="reference external" href="https://openreview.net/forum?id=JJuP86nBl4q">https://openreview.net/forum?id=JJuP86nBl4q</a></p>
</aside>
</aside>
</section>
<section id="parameters">
<h3>Parameters<a class="headerlink" href="#parameters" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>device<span class="classifier">torch.device, optional</span></dt><dd><p>Tensor device for acceleration, by default torch.device(“cpu”)</p>
</dd>
<dt>random_state: RandomState, optional</dt><dd><p>Random initial state, by default None</p>
</dd>
</dl>
</section>
<section id="mixins">
<h3>Mixins<a class="headerlink" href="#mixins" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>ModelLessMixin</dt><dd><p>Mixin for a data evaluator that doesn’t require a model or evaluation metric.</p>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="opendataval.dataval.lava.lava.LavaEvaluator.evaluate_data_values">
<span class="sig-name descname"><span class="pre">evaluate_data_values</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="headerlink" href="#opendataval.dataval.lava.lava.LavaEvaluator.evaluate_data_values" title="Link to this definition">#</a></dt>
<dd><p>Return data values for each training data point.</p>
<p>Gets the calibrated gradient of the dual solution, which can be interpreted as
the data values.</p>
<section id="returns">
<h4>Returns<a class="headerlink" href="#returns" title="Link to this heading">#</a></h4>
<dl class="simple">
<dt>np.ndarray</dt><dd><p>Predicted data values/selection for training input data point</p>
</dd>
</dl>
</section>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="opendataval.dataval.lava.lava.LavaEvaluator.train_data_values">
<span class="sig-name descname"><span class="pre">train_data_values</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.lava.LavaEvaluator.train_data_values" title="Link to this definition">#</a></dt>
<dd><p>Trains model to predict data values.</p>
<p>Computes the class-wise Wasserstein distance between the training and the
validation set.</p>
<section id="id2">
<h4>References<a class="headerlink" href="#id2" title="Link to this heading">#</a></h4>
<aside class="footnote-list brackets">
<aside class="footnote brackets" id="id3" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
<p>H. A. Just, F. Kang, T. Wang, Y. Zeng, M. Ko, M. Jin, and R. Jia,
LAVA: Data Valuation without Pre-Specified Learning Algorithms,
2023. Available: <a class="reference external" href="https://openreview.net/forum?id=JJuP86nBl4q">https://openreview.net/forum?id=JJuP86nBl4q</a></p>
</aside>
<aside class="footnote brackets" id="id4" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></span>
<p>D. Alvarez-Melis and N. Fusi,
Geometric Dataset Distances via Optimal Transport,
arXiv.org, 2020. Available: <a class="reference external" href="https://arxiv.org/abs/2002.02923">https://arxiv.org/abs/2002.02923</a>.</p>
</aside>
<aside class="footnote brackets" id="id5" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>3<span class="fn-bracket">]</span></span>
<p>D. Alvarez-Melis and N. Fusi,
Dataset Dynamics via Gradient Flows in Probability Space,
arXiv.org, 2020. Available: <a class="reference external" href="https://arxiv.org/abs/2010.12760">https://arxiv.org/abs/2010.12760</a>.</p>
</aside>
</aside>
</section>
</dd></dl>
</section>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="opendataval.dataval.lava.lava.macos_fix">
<span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.lava.</span></span><span class="sig-name descname"><span class="pre">macos_fix</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.lava.macos_fix" title="Link to this definition">#</a></dt>
<dd><p>Geomloss package has a bug on MacOS remedied as follows.</p>
<p><a href="#id18"><span class="problematic" id="id19">`Link to similar bug: https://github.com/NVlabs/stylegan3/issues/75`_</span></a>.</p>
</dd></dl>
</section>
<section id="module-opendataval.dataval.lava.otdd">
<span id="opendataval-dataval-lava-otdd-module"></span><h2>opendataval.dataval.lava.otdd module<a class="headerlink" href="#module-opendataval.dataval.lava.otdd" title="Link to this heading">#</a></h2>
<p>Main module for computing exact wasserstein distance between two data sets.</p>
<p><a class="reference external" href="https://github.com/microsoft/otdd">OTDD Repository</a>.</p>
<section id="id6">
<h3>References<a class="headerlink" href="#id6" title="Link to this heading">#</a></h3>
<blockquote>
<div><aside class="footnote-list brackets">
<aside class="footnote brackets" id="id7" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
<p>D. Alvarez-Melis and N. Fusi,
Geometric Dataset Distances via Optimal Transport,
arXiv.org, 2020. Available: <a class="reference external" href="https://arxiv.org/abs/2002.02923">https://arxiv.org/abs/2002.02923</a>.</p>
</aside>
<aside class="footnote brackets" id="id8" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></span>
<p>D. Alvarez-Melis and N. Fusi,
Dataset Dynamics via Gradient Flows in Probability Space,
arXiv.org, 2020. Available: <a class="reference external" href="https://arxiv.org/abs/2010.12760">https://arxiv.org/abs/2010.12760</a>.</p>
</aside>
<aside class="footnote brackets" id="id9" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span>3<span class="fn-bracket">]</span></span>
<p><a class="reference external" href="https://github.com/microsoft/otdd">OTDD repo</a>.
The following implementation was taken from this repository. It is intended as a
strict subset of the options provided in the repository, only computing the
class-wise Wasserstein as needed by the LAVA Paper by H.A. Just et al.</p>
</aside>
</aside>
</div></blockquote>
<dl class="simple">
<dt>Legacy notation:</dt><dd><p>X1, X2: feature tensors of the two datasets
Y1, Y2: label tensors of the two datasets
N1, N2 (or N,M): number of samples in datasets
D1, D2: (feature) dimension of the datasets
C1, C2: number of classes in the datasets</p>
</dd>
</dl>
</section>
<dl class="py class">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.DatasetDistance">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.otdd.</span></span><span class="sig-name descname"><span class="pre">DatasetDistance</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x_train</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_train</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">x_valid</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_valid</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">feature_cost</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'euclidean'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'euclidean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">entreg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lam_x</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lam_y</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_ot_loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sinkhorn'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_ot_debiased</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_ot_p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inner_ot_entreg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">device</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">device(type='cpu')</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.otdd.DatasetDistance" title="Link to this definition">#</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>The main class for the Optimal Transport Dataset Distance.</p>
<p>An object of this class is instantiated with two datasets (the source and
target), which are stored in it, and various arguments determining how the
exact Wasserstein distance is to be computed.</p>
<section id="id10">
<h3>Parameters<a class="headerlink" href="#id10" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>x_train<span class="classifier">torch.Tensor</span></dt><dd><p>Covariates of the first distribution</p>
</dd>
<dt>y_train<span class="classifier">torch.Tensor</span></dt><dd><p>Labels of the first distribution</p>
</dd>
<dt>x_valid<span class="classifier">torch.Tensor</span></dt><dd><p>Covariates of the second/validation distribution</p>
</dd>
<dt>y_valid<span class="classifier">torch.Tensor</span></dt><dd><p>Labels of the second/validation distribution</p>
</dd>
<dt>feature_cost<span class="classifier">Literal[“euclidean”] | Callable, optional</span></dt><dd><p>If not ‘euclidean’, must be a callable that implements a cost function
between feature vectors, by default “euclidean”</p>
</dd>
<dt>p<span class="classifier">int, optional</span></dt><dd><p>The coefficient in the OT cost (i.e., the p in p-Wasserstein), by default 2</p>
</dd>
<dt>entreg<span class="classifier">float, optional</span></dt><dd><p>The strength of entropy regularization for sinkhorn, by default 0.1</p>
</dd>
<dt>lam_x<span class="classifier">float, optional</span></dt><dd><p>Weight parameter for feature component of distance, by default 1.0</p>
</dd>
<dt>lam_y<span class="classifier">float, optional</span></dt><dd><p>Weight parameter for label component of distance.=, by default 1.0</p>
</dd>
<dt>inner_ot_loss<span class="classifier">str, optional</span></dt><dd><p>Loss type to exact OT problem, by default “sinkhorn”</p>
</dd>
<dt>inner_ot_debiased<span class="classifier">bool, optional</span></dt><dd><p>Whether to use the debiased version of sinkhorn in the inner OT problem,
by default False</p>
</dd>
<dt>inner_ot_p<span class="classifier">int, optional</span></dt><dd><p>The coefficient in the inner OT cost., by default 2</p>
</dd>
<dt>inner_ot_entreg<span class="classifier">float, optional</span></dt><dd><p>The strength of entropy regularization for sinkhorn in the inner OT problem,
by default 0.1</p>
</dd>
<dt>device<span class="classifier">torch.device, optional</span></dt><dd><p>Tensor device for acceleration, by default torch.device(“cpu”)</p>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.DatasetDistance.dual_sol">
<span class="sig-name descname"><span class="pre">dual_sol</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#opendataval.dataval.lava.otdd.DatasetDistance.dual_sol" title="Link to this definition">#</a></dt>
<dd><p>Compute dataset distance.</p>
<dl class="simple">
<dt>Note:</dt><dd><p>Currently requires fully loading dataset into memory, this can probably be
avoided, e.g., via subsampling.</p>
</dd>
</dl>
<section id="id11">
<h4>Returns<a class="headerlink" href="#id11" title="Link to this heading">#</a></h4>
<dl class="simple">
<dt>tuple[float, torch.Tensor]</dt><dd><p>dist (float): the optimal transport dataset distance value.
pi (tensor, optional): the optimal transport coupling.</p>
</dd>
</dl>
</section>
</dd></dl>
</section>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.FeatureCost">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.otdd.</span></span><span class="sig-name descname"><span class="pre">FeatureCost</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">src_embedding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tgt_embedding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">src_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tgt_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cpu'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.otdd.FeatureCost" title="Link to this definition">#</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Class implementing a cost (or distance) between feature vectors.</p>
<dl>
<dt>Arguments:</dt><dd><p>p (int): the coefficient in the OT cost (i.e., the p in p-Wasserstein).
src_embedding (callable, optional): if provided, source data will be</p>
<blockquote>
<div><p>embedded using this function prior to distance computation.</p>
</div></blockquote>
<dl class="simple">
<dt>tgt_embedding (callable, optional): if provided, target data will be</dt><dd><p>embedded using this function prior to distance computation.</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.batch_augmented_cost">
<span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.otdd.</span></span><span class="sig-name descname"><span class="pre">batch_augmented_cost</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">Z1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Z2</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">W</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">feature_cost</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lam_x</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lam_y</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.otdd.batch_augmented_cost" title="Link to this definition">#</a></dt>
<dd><p>Batch ground cost computation on augmented datasets.</p>
<section id="id12">
<h3>Parameters<a class="headerlink" href="#id12" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>Z1<span class="classifier">torch.Tensor</span></dt><dd><p>Tensor of size (B,N,D1), where last position in last dim corresponds to label Y.</p>
</dd>
<dt>Z2<span class="classifier">torch.Tensor</span></dt><dd><p>Tensor of size (B,M,D2), where last position in last dim corresponds to label Y.</p>
</dd>
<dt>W<span class="classifier">torch.Tensor, optional</span></dt><dd><p>Tensor of size (V1,V2) of precomputed pairwise label distances for all labels
V1,V2 and returns a batched cost matrix as a (B,N,M) Tensor. W is expected to be
congruent with p. I.e, if p=2, W[i,j] should be squared Wasserstein distance.,
by default None</p>
</dd>
<dt>feature_cost<span class="classifier">str, optional</span></dt><dd><p>if None or ‘euclidean’, uses euclidean distances as feature metric,
otherwise uses this function as metric., by default None</p>
</dd>
<dt>p<span class="classifier">int, optional</span></dt><dd><p>Power of the cost (i.e. order of p-Wasserstein distance), by default 2</p>
</dd>
<dt>lam_x<span class="classifier">float, optional</span></dt><dd><p>Weight parameter for feature component of distance, by default 1.0</p>
</dd>
<dt>lam_y<span class="classifier">float, optional</span></dt><dd><p>Weight parameter for label component of distance, by default 1.0</p>
</dd>
</dl>
</section>
<section id="id13">
<h3>Returns<a class="headerlink" href="#id13" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>torch.Tensor</dt><dd><p>torch Tensor of size (B,N,M)</p>
</dd>
</dl>
</section>
<section id="raises">
<h3>Raises<a class="headerlink" href="#raises" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>ValueError</dt><dd><p>If W is not provided</p>
</dd>
</dl>
</section>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.extract_dataset">
<span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.otdd.</span></span><span class="sig-name descname"><span class="pre">extract_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x_input</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y_input</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reindex_start</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Tensor</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#opendataval.dataval.lava.otdd.extract_dataset" title="Link to this definition">#</a></dt>
<dd><p>Loads full dataset into memory and reindexes the labels.</p>
<section id="id14">
<h3>Parameters<a class="headerlink" href="#id14" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>x_input<span class="classifier">Dataset | torch.Tensor</span></dt><dd><p>Covariate Dataset/tensor to be loaded</p>
</dd>
<dt>y_input<span class="classifier">Dataset | torch.Tensor</span></dt><dd><p>Label Dataset/tensor to be loaded</p>
</dd>
<dt>batch_size<span class="classifier">int, optional</span></dt><dd><p>Batch size of data to be loaded at a time, by default 256</p>
</dd>
<dt>reindex_start<span class="classifier">int, optional</span></dt><dd><p>How much to offset the labels by, useful when comparing different
data sets so that the data have different labels, by default 0</p>
</dd>
</dl>
</section>
<section id="id15">
<h3>Returns<a class="headerlink" href="#id15" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>tuple[torch.Tensor, torch.Tensor]</dt><dd><p><strong>x_tensor</strong> Covariates stacked along first dimension
<strong>y_tensor</strong> Labels, no longer in one-hot-encoding and offset by reindex_start</p>
</dd>
</dl>
</section>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="opendataval.dataval.lava.otdd.pwdist_exact">
<span class="sig-prename descclassname"><span class="pre">opendataval.dataval.lava.otdd.</span></span><span class="sig-name descname"><span class="pre">pwdist_exact</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">X2</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Y2</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">symmetric</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sinkhorn'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cost_function</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'euclidean'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'euclidean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">debias</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">entreg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">device</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">device(type='cpu')</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#opendataval.dataval.lava.otdd.pwdist_exact" title="Link to this definition">#</a></dt>
<dd><p>Computation of pairwise Wasserstein distances.</p>
<p>Efficient computation of pairwise label-to-label Wasserstein distances
between multiple distributions, without using Gaussian assumption.</p>
<section id="id16">
<h3>Parameters<a class="headerlink" href="#id16" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>X1<span class="classifier">torch.Tensor</span></dt><dd><p>Covariates of first distribution</p>
</dd>
<dt>Y1<span class="classifier">torch.Tensor</span></dt><dd><p>Labels of first distribution</p>
</dd>
<dt>X2<span class="classifier">torch.Tensor, optional</span></dt><dd><p>Covariates of second distribution, if None distributions are treated as same,
by default None</p>
</dd>
<dt>Y2<span class="classifier">torch.Tensor, optional</span></dt><dd><p>Labels of second distribution, iif None distributions are treated as same,
by default None</p>
</dd>
<dt>symmetric<span class="classifier">bool, optional</span></dt><dd><p>Whether X1/Y1 and X2/Y2 are to be treated as the same dataset, by default False</p>
</dd>
<dt>loss<span class="classifier">str, optional</span></dt><dd><p>The loss function to compute. Sinkhorn divergence, which interpolates between
(blur=0) and kernel (blur= <span class="math notranslate nohighlight">\(+\infty\)</span> ) distances., by default “sinkhorn”</p>
</dd>
<dt>cost_function<span class="classifier">: Literal[“euclidean”] | Callable[…, torch.Tensor], optional</span></dt><dd><p>Cost function that should be used instead of <span class="math notranslate nohighlight">\(\tfrac{1}{p}\|x-y\|^p\)</span>,
by default “euclidean”</p>
</dd>
<dt>p<span class="classifier">int, optional</span></dt><dd><p>power of the cost (i.e. order of p-Wasserstein distance), by default 2</p>
</dd>
<dt>debias<span class="classifier">bool, optional</span></dt><dd><p>If true, uses debiased sinkhorn divergence., by default True</p>
</dd>
<dt>entreg<span class="classifier">float, optional</span></dt><dd><p>The strength of entropy regularization for sinkhorn., by default 1e-1</p>
</dd>
<dt>device<span class="classifier">torch.device, optional</span></dt><dd><p>Tensor device for acceleration, by default torch.device(“cpu”)</p>
</dd>
</dl>
</section>
<section id="id17">
<h3>Returns<a class="headerlink" href="#id17" title="Link to this heading">#</a></h3>
<dl class="simple">
<dt>torch.Tensor</dt><dd><p>Computed Wasserstein distance</p>
</dd>
</dl>
</section>
</dd></dl>
</section>
<section id="module-opendataval.dataval.lava">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-opendataval.dataval.lava" title="Link to this heading">#</a></h2>
</section>
</section>
</article>
</div>
<footer>
<div class="related-pages">
<a class="next-page" href="opendataval.dataval.margcontrib.html">
<div class="page-info">
<div class="context">
<span>Next</span>
</div>
<div class="title">opendataval.dataval.margcontrib package</div>
</div>
<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
</a>
<a class="prev-page" href="opendataval.dataval.knnshap.html">
<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
<div class="page-info">
<div class="context">
<span>Previous</span>
</div>
<div class="title">opendataval.dataval.knnshap package</div>
</div>
</a>
</div>
<div class="bottom-of-page">
<div class="left-details">
<div class="copyright">
Copyright © 2023, OpenDataVal
</div>
Made with <a href="https://www.sphinx-doc.org/">Sphinx</a> and <a class="muted-link" href="https://pradyunsg.me">@pradyunsg</a>'s
<a href="https://github.com/pradyunsg/furo">Furo</a>
</div>
<div class="right-details">
</div>
</div>
</footer>
</div>
<aside class="toc-drawer">
<div class="toc-sticky toc-scroll">
<div class="toc-title-container">
<span class="toc-title">
On this page
</span>
</div>
<div class="toc-tree-container">
<div class="toc-tree">
<ul>
<li><a class="reference internal" href="#">opendataval.dataval.lava package</a><ul>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-opendataval.dataval.lava.lava">opendataval.dataval.lava.lava module</a><ul>
<li><a class="reference internal" href="#opendataval.dataval.lava.lava.LavaEvaluator"><code class="docutils literal notranslate"><span class="pre">LavaEvaluator</span></code></a><ul>
<li><a class="reference internal" href="#opendataval.dataval.lava.lava.LavaEvaluator.evaluate_data_values"><code class="docutils literal notranslate"><span class="pre">LavaEvaluator.evaluate_data_values()</span></code></a></li>
<li><a class="reference internal" href="#opendataval.dataval.lava.lava.LavaEvaluator.train_data_values"><code class="docutils literal notranslate"><span class="pre">LavaEvaluator.train_data_values()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#opendataval.dataval.lava.lava.macos_fix"><code class="docutils literal notranslate"><span class="pre">macos_fix()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-opendataval.dataval.lava.otdd">opendataval.dataval.lava.otdd module</a><ul>
<li><a class="reference internal" href="#id6">References</a></li>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.DatasetDistance"><code class="docutils literal notranslate"><span class="pre">DatasetDistance</span></code></a><ul>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.DatasetDistance.dual_sol"><code class="docutils literal notranslate"><span class="pre">DatasetDistance.dual_sol()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.FeatureCost"><code class="docutils literal notranslate"><span class="pre">FeatureCost</span></code></a></li>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.batch_augmented_cost"><code class="docutils literal notranslate"><span class="pre">batch_augmented_cost()</span></code></a></li>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.extract_dataset"><code class="docutils literal notranslate"><span class="pre">extract_dataset()</span></code></a></li>
<li><a class="reference internal" href="#opendataval.dataval.lava.otdd.pwdist_exact"><code class="docutils literal notranslate"><span class="pre">pwdist_exact()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-opendataval.dataval.lava">Module contents</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</aside>
</div>
</div><script src="_static/documentation_options.js?v=7f41d439"></script>
<script src="_static/doctools.js?v=888ff710"></script>
<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
<script src="_static/scripts/furo.js?v=32e29ea5"></script>
<script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
</body>
</html>