-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathtesting.html
926 lines (738 loc) · 68.7 KB
/
testing.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
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
<!DOCTYPE html>
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
<head>
<meta name="robots" content="noindex">
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>torch.testing — PyTorch 1.9.1 documentation</title>
<link rel="canonical" href="https://pytorch.org/docs/stable/testing.html"/>
<link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
<!-- <link rel="stylesheet" href="_static/pygments.css" type="text/css" /> -->
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css" type="text/css" />
<link rel="stylesheet" href="_static/css/jit.css" type="text/css" />
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css" type="text/css" />
<link rel="stylesheet" href="_static/katex-math.css" type="text/css" />
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
<link rel="next" title="Benchmark Utils - torch.utils.benchmark" href="benchmark_utils.html" />
<link rel="prev" title="torch.Storage" href="storage.html" />
<!-- Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-117752657-2');
</script>
<!-- End Google Analytics -->
<script src="_static/js/modernizr.min.js"></script>
<!-- Preload the theme fonts -->
<link rel="preload" href="_static/fonts/FreightSans/freight-sans-book.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="_static/fonts/FreightSans/freight-sans-medium.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="_static/fonts/IBMPlexMono/IBMPlexMono-Medium.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="_static/fonts/FreightSans/freight-sans-bold.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="_static/fonts/FreightSans/freight-sans-medium-italic.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="_static/fonts/IBMPlexMono/IBMPlexMono-SemiBold.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<!-- Preload the katex fonts -->
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Math-Italic.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Main-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Main-Bold.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Size1-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Size4-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Size2-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Size3-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/fonts/KaTeX_Caligraphic-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.15.2/css/all.css" integrity="sha384-vSIIfh2YWi9wW0r9iZe7RJPrKwp6bG+s9QZMoITbCckVJqGCCRhc+ccxNcdpHuYu" crossorigin="anonymous">
</head>
<div class="container-fluid header-holder tutorials-header" id="header-holder">
<div class="container">
<div class="header-container">
<a class="header-logo" href="https://pytorch.org/" aria-label="PyTorch"></a>
<div class="main-menu">
<ul>
<li>
<a href="https://pytorch.org/get-started">Get Started</a>
</li>
<li>
<a href="https://pytorch.org/ecosystem">Ecosystem</a>
</li>
<li>
<a href="https://pytorch.org/mobile">Mobile</a>
</li>
<li>
<a href="https://pytorch.org/blog/">Blog</a>
</li>
<li>
<a href="https://pytorch.org/tutorials">Tutorials</a>
</li>
<li class="active docs-active">
<div id="resourcesDropdownButton" data-toggle="resources-dropdown" class="resources-dropdown">
<a class="resource-option with-down-orange-arrow">
Docs
</a>
<div class="resources-dropdown-menu">
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/docs/stable/index.html">
<span class="dropdown-title">PyTorch</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/audio/stable/index.html">
<span class="dropdown-title">torchaudio</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/text/stable/index.html">
<span class="dropdown-title">torchtext</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/vision/stable/index.html">
<span class="dropdown-title">torchvision</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/elastic/">
<span class="dropdown-title">TorchElastic</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/serve/">
<span class="dropdown-title">TorchServe</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/xla">
<span class="dropdown-title">PyTorch on XLA Devices</span>
<p></p>
</a>
</div>
</li>
<li>
<div id="resourcesDropdownButton" data-toggle="resources-dropdown" class="resources-dropdown">
<a class="resource-option with-down-arrow">
Resources
</a>
<div class="resources-dropdown-menu">
<a class="nav-dropdown-item" href="https://pytorch.org/features">
<span class="dropdown-title">About</span>
<p>Learn about PyTorch’s features and capabilities</p>
</a>
<a class="nav-dropdown-item" href="https://pytorch.org/#community-module">
<span class="dropdown-title">Community</span>
<p>Join the PyTorch developer community to contribute, learn, and get your questions answered.</p>
</a>
<a class="nav-dropdown-item" href="https://pytorch.org/resources">
<span class="dropdown-title">Developer Resources</span>
<p>Find resources and get questions answered</p>
</a>
<a class="nav-dropdown-item" href="https://discuss.pytorch.org/" target="_blank">
<span class="dropdown-title">Forums</span>
<p>A place to discuss PyTorch code, issues, install, research</p>
</a>
<a class="nav-dropdown-item" href="https://pytorch.org/hub">
<span class="dropdown-title">Models (Beta)</span>
<p>Discover, publish, and reuse pre-trained models</p>
</a>
</div>
</div>
</li>
<li>
<a href="https://github.com/pytorch/pytorch">GitHub</a>
</li>
</ul>
</div>
<a class="main-menu-open-button" href="#" data-behavior="open-mobile-menu"></a>
</div>
</div>
</div>
<body class="pytorch-body">
<div class="table-of-contents-link-wrapper">
<span>Table of Contents</span>
<a href="#" class="toggle-table-of-contents" data-behavior="toggle-table-of-contents"></a>
</div>
<nav data-toggle="wy-nav-shift" class="pytorch-left-menu" id="pytorch-left-menu">
<div class="pytorch-side-scroll">
<div class="pytorch-menu pytorch-menu-vertical" data-spy="affix" role="navigation" aria-label="main navigation">
<div class="pytorch-left-menu-search">
<div class="version">
<a href='https://pytorch.org/docs/versions.html'>1.9.1 ▼</a>
</div>
<div role="search">
<form id="rtd-search-form" class="wy-form" action="search.html" method="get">
<input type="text" name="q" placeholder="Search Docs" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div>
<p class="caption"><span class="caption-text">Notes</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">Automatic Mixed Precision examples</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/broadcasting.html">Broadcasting semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/cpu_threading_torchscript_inference.html">CPU threading and TorchScript inference</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/cuda.html">CUDA semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/ddp.html">Distributed Data Parallel</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/extending.html">Extending PyTorch</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/faq.html">Frequently Asked Questions</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/gradcheck.html">Gradcheck mechanics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/hip.html">HIP (ROCm) semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/modules.html">Modules</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/multiprocessing.html">Multiprocessing best practices</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/randomness.html">Reproducibility</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/serialization.html">Serialization semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/windows.html">Windows FAQ</a></li>
</ul>
<p class="caption"><span class="caption-text">Language Bindings</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="cpp_index.html">C++</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/javadoc/">Javadoc</a></li>
</ul>
<p class="caption"><span class="caption-text">Python API</span></p>
<ul class="current">
<li class="toctree-l1"><a class="reference internal" href="torch.html">torch</a></li>
<li class="toctree-l1"><a class="reference internal" href="nn.html">torch.nn</a></li>
<li class="toctree-l1"><a class="reference internal" href="nn.functional.html">torch.nn.functional</a></li>
<li class="toctree-l1"><a class="reference internal" href="tensors.html">torch.Tensor</a></li>
<li class="toctree-l1"><a class="reference internal" href="tensor_attributes.html">Tensor Attributes</a></li>
<li class="toctree-l1"><a class="reference internal" href="tensor_view.html">Tensor Views</a></li>
<li class="toctree-l1"><a class="reference internal" href="autograd.html">torch.autograd</a></li>
<li class="toctree-l1"><a class="reference internal" href="cuda.html">torch.cuda</a></li>
<li class="toctree-l1"><a class="reference internal" href="amp.html">torch.cuda.amp</a></li>
<li class="toctree-l1"><a class="reference internal" href="backends.html">torch.backends</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributed.html">torch.distributed</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributed.elastic.html">torch.distributed.elastic</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributed.optim.html">torch.distributed.optim</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributions.html">torch.distributions</a></li>
<li class="toctree-l1"><a class="reference internal" href="fft.html">torch.fft</a></li>
<li class="toctree-l1"><a class="reference internal" href="futures.html">torch.futures</a></li>
<li class="toctree-l1"><a class="reference internal" href="fx.html">torch.fx</a></li>
<li class="toctree-l1"><a class="reference internal" href="hub.html">torch.hub</a></li>
<li class="toctree-l1"><a class="reference internal" href="jit.html">torch.jit</a></li>
<li class="toctree-l1"><a class="reference internal" href="linalg.html">torch.linalg</a></li>
<li class="toctree-l1"><a class="reference internal" href="special.html">torch.special</a></li>
<li class="toctree-l1"><a class="reference internal" href="torch.overrides.html">torch.overrides</a></li>
<li class="toctree-l1"><a class="reference internal" href="package.html">torch.package</a></li>
<li class="toctree-l1"><a class="reference internal" href="profiler.html">torch.profiler</a></li>
<li class="toctree-l1"><a class="reference internal" href="nn.init.html">torch.nn.init</a></li>
<li class="toctree-l1"><a class="reference internal" href="onnx.html">torch.onnx</a></li>
<li class="toctree-l1"><a class="reference internal" href="optim.html">torch.optim</a></li>
<li class="toctree-l1"><a class="reference internal" href="complex_numbers.html">Complex Numbers</a></li>
<li class="toctree-l1"><a class="reference internal" href="ddp_comm_hooks.html">DDP Communication Hooks</a></li>
<li class="toctree-l1"><a class="reference internal" href="pipeline.html">Pipeline Parallelism</a></li>
<li class="toctree-l1"><a class="reference internal" href="quantization.html">Quantization</a></li>
<li class="toctree-l1"><a class="reference internal" href="rpc.html">Distributed RPC Framework</a></li>
<li class="toctree-l1"><a class="reference internal" href="random.html">torch.random</a></li>
<li class="toctree-l1"><a class="reference internal" href="sparse.html">torch.sparse</a></li>
<li class="toctree-l1"><a class="reference internal" href="storage.html">torch.Storage</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">torch.testing</a></li>
<li class="toctree-l1"><a class="reference internal" href="benchmark_utils.html">torch.utils.benchmark</a></li>
<li class="toctree-l1"><a class="reference internal" href="bottleneck.html">torch.utils.bottleneck</a></li>
<li class="toctree-l1"><a class="reference internal" href="checkpoint.html">torch.utils.checkpoint</a></li>
<li class="toctree-l1"><a class="reference internal" href="cpp_extension.html">torch.utils.cpp_extension</a></li>
<li class="toctree-l1"><a class="reference internal" href="data.html">torch.utils.data</a></li>
<li class="toctree-l1"><a class="reference internal" href="dlpack.html">torch.utils.dlpack</a></li>
<li class="toctree-l1"><a class="reference internal" href="mobile_optimizer.html">torch.utils.mobile_optimizer</a></li>
<li class="toctree-l1"><a class="reference internal" href="model_zoo.html">torch.utils.model_zoo</a></li>
<li class="toctree-l1"><a class="reference internal" href="tensorboard.html">torch.utils.tensorboard</a></li>
<li class="toctree-l1"><a class="reference internal" href="type_info.html">Type Info</a></li>
<li class="toctree-l1"><a class="reference internal" href="named_tensor.html">Named Tensors</a></li>
<li class="toctree-l1"><a class="reference internal" href="name_inference.html">Named Tensors operator coverage</a></li>
<li class="toctree-l1"><a class="reference internal" href="__config__.html">torch.__config__</a></li>
</ul>
<p class="caption"><span class="caption-text">Libraries</span></p>
<ul>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/audio/stable">torchaudio</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/text/stable">torchtext</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/vision/stable">torchvision</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/serve">TorchServe</a></li>
<li class="toctree-l1"><a class="reference external" href="http://pytorch.org/xla/">PyTorch on XLA Devices</a></li>
</ul>
<p class="caption"><span class="caption-text">Community</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="community/contribution_guide.html">PyTorch Contribution Guide</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/governance.html">PyTorch Governance</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/persons_of_interest.html">PyTorch Governance | Persons of Interest</a></li>
</ul>
</div>
</div>
</nav>
<div class="pytorch-container">
<div class="pytorch-page-level-bar" id="pytorch-page-level-bar">
<div class="pytorch-breadcrumbs-wrapper">
<div role="navigation" aria-label="breadcrumbs navigation">
<ul class="pytorch-breadcrumbs">
<li>
<a href="index.html">
Docs
</a> >
</li>
<li>torch.testing</li>
<li class="pytorch-breadcrumbs-aside">
<a href="_sources/testing.rst.txt" rel="nofollow"><img src="_static/images/view-page-source-icon.svg"></a>
</li>
</ul>
</div>
</div>
<div class="pytorch-shortcuts-wrapper" id="pytorch-shortcuts-wrapper">
Shortcuts
</div>
</div>
<section data-toggle="wy-nav-shift" id="pytorch-content-wrap" class="pytorch-content-wrap">
<div class="pytorch-content-left">
<div class="rst-content">
<div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article">
<article itemprop="articleBody" id="pytorch-article" class="pytorch-article">
<div class="section" id="torch-testing">
<h1>torch.testing<a class="headerlink" href="#torch-testing" title="Permalink to this headline">¶</a></h1>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>This module is in a PROTOTYPE state. New functions are still being added, and the available functions may change in
future PyTorch releases. We are actively looking for feedback for UI/UX improvements or missing functionalities.</p>
</div>
<span class="target" id="module-torch.testing"></span><dl class="function">
<dt id="torch.testing.assert_close">
<code class="sig-prename descclassname">torch.testing.</code><code class="sig-name descname">assert_close</code><span class="sig-paren">(</span><em class="sig-param">actual</em>, <em class="sig-param">expected</em>, <em class="sig-param">*</em>, <em class="sig-param">rtol=None</em>, <em class="sig-param">atol=None</em>, <em class="sig-param">equal_nan=False</em>, <em class="sig-param">check_device=True</em>, <em class="sig-param">check_dtype=True</em>, <em class="sig-param">check_stride=True</em>, <em class="sig-param">msg=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/testing/_asserts.html#assert_close"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.testing.assert_close" title="Permalink to this definition">¶</a></dt>
<dd><p>Asserts that <code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> are close.</p>
<p>If <code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> are real-valued and finite, they are considered close if</p>
<div class="math">
<span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><mo stretchy="false">∣</mo><mtext>actual</mtext><mo>−</mo><mtext>expected</mtext><mo stretchy="false">∣</mo><mo>≤</mo><mtext mathvariant="monospace">atol</mtext><mo>+</mo><mtext mathvariant="monospace">rtol</mtext><mo>⋅</mo><mo stretchy="false">∣</mo><mtext>expected</mtext><mo stretchy="false">∣</mo></mrow><annotation encoding="application/x-tex">\lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">∣</span><span class="mord text"><span class="mord">actual</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">expected</span></span><span class="mclose">∣</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">≤</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.6944400000000001em;vertical-align:-0.08333em;"></span><span class="mord text"><span class="mord texttt">atol</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.61111em;vertical-align:0em;"></span><span class="mord text"><span class="mord texttt">rtol</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">⋅</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">∣</span><span class="mord text"><span class="mord">expected</span></span><span class="mclose">∣</span></span></span></span></span></div><p>and they have the same <a class="reference internal" href="generated/torch.Tensor.device.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">device</span></code></a> (if <code class="xref py py-attr docutils literal notranslate"><span class="pre">check_device</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>), same <code class="docutils literal notranslate"><span class="pre">dtype</span></code> (if
<code class="xref py py-attr docutils literal notranslate"><span class="pre">check_dtype</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>), and the same stride (if <code class="xref py py-attr docutils literal notranslate"><span class="pre">check_stride</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>). Non-finite values
(<code class="docutils literal notranslate"><span class="pre">-inf</span></code> and <code class="docutils literal notranslate"><span class="pre">inf</span></code>) are only considered close if and only if they are equal. <code class="docutils literal notranslate"><span class="pre">NaN</span></code>’s are only considered equal
to each other if <code class="xref py py-attr docutils literal notranslate"><span class="pre">equal_nan</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p>
<p>If <code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> are complex-valued, they are considered close if both their real and
imaginary components are considered close according to the definition above.</p>
<p><code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> can be <a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>’s or any array-or-scalar-like of the same type,
from which <a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a>’s can be constructed with <a class="reference internal" href="generated/torch.as_tensor.html#torch.as_tensor" title="torch.as_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.as_tensor()</span></code></a>. In addition, <code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and
<code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> can be <a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Sequence</span></code></a>’s or <a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Mapping</span></code></a>’s in which case
they are considered close if their structure matches and all their elements are considered close according to the
above definition.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>actual</strong> (<em>Any</em>) – Actual input.</p></li>
<li><p><strong>expected</strong> (<em>Any</em>) – Expected input.</p></li>
<li><p><strong>rtol</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a><em>]</em>) – Relative tolerance. If specified <code class="xref py py-attr docutils literal notranslate"><span class="pre">atol</span></code> must also be specified. If omitted,
default values based on the <code class="xref py py-attr docutils literal notranslate"><span class="pre">dtype</span></code> are selected with the below table.</p></li>
<li><p><strong>atol</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a><em>]</em>) – Absolute tolerance. If specified <code class="xref py py-attr docutils literal notranslate"><span class="pre">rtol</span></code> must also be specified. If omitted,
default values based on the <code class="xref py py-attr docutils literal notranslate"><span class="pre">dtype</span></code> are selected with the below table.</p></li>
<li><p><strong>equal_nan</strong> (<em>Union</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a><em>]</em>) – If <code class="docutils literal notranslate"><span class="pre">True</span></code>, two <code class="docutils literal notranslate"><span class="pre">NaN</span></code> values will be considered equal. If <code class="docutils literal notranslate"><span class="pre">"relaxed"</span></code>,
complex values are considered as <code class="docutils literal notranslate"><span class="pre">NaN</span></code> if either the real <strong>or</strong> imaginary component is <code class="docutils literal notranslate"><span class="pre">NaN</span></code>.</p></li>
<li><p><strong>check_device</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a>) – If <code class="docutils literal notranslate"><span class="pre">True</span></code> (default), asserts that corresponding tensors are on the same
<a class="reference internal" href="generated/torch.Tensor.device.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">device</span></code></a>. If this check is disabled, tensors on different
<a class="reference internal" href="generated/torch.Tensor.device.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">device</span></code></a>’s are moved to the CPU before being compared.</p></li>
<li><p><strong>check_dtype</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a>) – If <code class="docutils literal notranslate"><span class="pre">True</span></code> (default), asserts that corresponding tensors have the same <code class="docutils literal notranslate"><span class="pre">dtype</span></code>. If this
check is disabled, tensors with different <code class="docutils literal notranslate"><span class="pre">dtype</span></code>’s are promoted to a common <code class="docutils literal notranslate"><span class="pre">dtype</span></code> (according to
<a class="reference internal" href="generated/torch.promote_types.html#torch.promote_types" title="torch.promote_types"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.promote_types()</span></code></a>) before being compared.</p></li>
<li><p><strong>check_stride</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a>) – If <code class="docutils literal notranslate"><span class="pre">True</span></code> (default), asserts that corresponding tensors have the same stride.</p></li>
<li><p><strong>msg</strong> (<em>Optional</em><em>[</em><em>Union</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a><em>, </em><em>Callable</em><em>[</em><em>[</em><a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>, </em><em>DiagnosticInfo</em><em>]</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a><em>]</em><em>]</em><em>]</em>) – Optional error message to use if
the values of corresponding tensors mismatch. Can be passed as callable in which case it will be called
with the mismatching tensors and a namespace of diagnostic info about the mismatches. See below for details.</p></li>
</ul>
</dd>
<dt class="field-even">Raises</dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>UsageError</strong> – If a <a class="reference internal" href="tensors.html#torch.Tensor" title="torch.Tensor"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.Tensor</span></code></a> can’t be constructed from an array-or-scalar-like.</p></li>
<li><p><strong>UsageError</strong> – If any tensor is quantized or sparse. This is a temporary restriction and will be relaxed in the
future.</p></li>
<li><p><strong>UsageError</strong> – If only <code class="xref py py-attr docutils literal notranslate"><span class="pre">rtol</span></code> or <code class="xref py py-attr docutils literal notranslate"><span class="pre">atol</span></code> is specified.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If corresponding array-likes have different types.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If the inputs are <a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Sequence</span></code></a>’s, but their length does not match.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If the inputs are <a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Mapping</span></code></a>’s, but their set of keys do not match.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If corresponding tensors do not have the same <code class="xref py py-attr docutils literal notranslate"><span class="pre">shape</span></code>.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If <code class="xref py py-attr docutils literal notranslate"><span class="pre">check_device</span></code>, but corresponding tensors are not on the same
<a class="reference internal" href="generated/torch.Tensor.device.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">device</span></code></a>.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If <code class="xref py py-attr docutils literal notranslate"><span class="pre">check_dtype</span></code>, but corresponding tensors do not have the same <code class="docutils literal notranslate"><span class="pre">dtype</span></code>.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If <code class="xref py py-attr docutils literal notranslate"><span class="pre">check_stride</span></code>, but corresponding tensors do not have the same stride.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/exceptions.html#AssertionError" title="(in Python v3.9)"><strong>AssertionError</strong></a> – If the values of corresponding tensors are not close.</p></li>
</ul>
</dd>
</dl>
<p>The following table displays the default <code class="docutils literal notranslate"><span class="pre">rtol</span></code> and <code class="docutils literal notranslate"><span class="pre">atol</span></code> for different <code class="docutils literal notranslate"><span class="pre">dtype</span></code>’s. Note that the <code class="docutils literal notranslate"><span class="pre">dtype</span></code>
refers to the promoted type in case <code class="xref py py-attr docutils literal notranslate"><span class="pre">actual</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">expected</span></code> do not have the same <code class="docutils literal notranslate"><span class="pre">dtype</span></code>.</p>
<table class="docutils colwidths-auto align-default">
<thead>
<tr class="row-odd"><th class="head"><p><code class="docutils literal notranslate"><span class="pre">dtype</span></code></p></th>
<th class="head"><p><code class="docutils literal notranslate"><span class="pre">rtol</span></code></p></th>
<th class="head"><p><code class="docutils literal notranslate"><span class="pre">atol</span></code></p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">float16</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-3</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-5</span></code></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">bfloat16</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1.6e-2</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-5</span></code></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">float32</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1.3e-6</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-5</span></code></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">float64</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-7</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-7</span></code></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">complex32</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-3</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-5</span></code></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">complex64</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1.3e-6</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-5</span></code></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">complex128</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-7</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">1e-7</span></code></p></td>
</tr>
<tr class="row-odd"><td><p>other</p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">0.0</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">0.0</span></code></p></td>
</tr>
</tbody>
</table>
<p>The namespace of diagnostic information that will be passed to <code class="xref py py-attr docutils literal notranslate"><span class="pre">msg</span></code> if its a callable has the following
attributes:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">number_of_elements</span></code> (int): Number of elements in each tensor being compared.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">total_mismatches</span></code> (int): Total number of mismatches.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">mismatch_ratio</span></code> (float): Total mismatches divided by number of elements.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">max_abs_diff</span></code> (Union[int, float]): Greatest absolute difference of the inputs.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">max_abs_diff_idx</span></code> (Union[int, Tuple[int, …]]): Index of greatest absolute difference.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">max_rel_diff</span></code> (Union[int, float]): Greatest relative difference of the inputs.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">max_rel_diff_idx</span></code> (Union[int, Tuple[int, …]]): Index of greatest relative difference.</p></li>
</ul>
<p>For <code class="docutils literal notranslate"><span class="pre">max_abs_diff</span></code> and <code class="docutils literal notranslate"><span class="pre">max_rel_diff</span></code> the type depends on the <code class="xref py py-attr docutils literal notranslate"><span class="pre">dtype</span></code> of the inputs.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># tensor to tensor comparison</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1e0</span><span class="p">,</span> <span class="mf">1e-1</span><span class="p">,</span> <span class="mf">1e-2</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">acos</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">expected</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># scalar to scalar comparison</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">math</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">math</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mf">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="mf">2.0</span> <span class="o">/</span> <span class="n">math</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mf">2.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># numpy array to numpy array comparison</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">1e0</span><span class="p">,</span> <span class="mf">1e-1</span><span class="p">,</span> <span class="mf">1e-2</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arccos</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">expected</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># sequence to sequence comparison</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">>>> </span><span class="c1"># The types of the sequences do not have to match. They only have to have the same</span>
<span class="gp">>>> </span><span class="c1"># length and their elements have to match.</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">]),</span> <span class="mf">2.0</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="mf">3.0</span><span class="p">)]</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">expected</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># mapping to mapping comparison</span>
<span class="gp">>>> </span><span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">OrderedDict</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">>>> </span><span class="n">foo</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">bar</span> <span class="o">=</span> <span class="mf">2.0</span>
<span class="gp">>>> </span><span class="n">baz</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="mf">3.0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># The types and a possible ordering of mappings do not have to match. They only</span>
<span class="gp">>>> </span><span class="c1"># have to have the same set of keys and their elements have to match.</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">OrderedDict</span><span class="p">([(</span><span class="s2">"foo"</span><span class="p">,</span> <span class="n">foo</span><span class="p">),</span> <span class="p">(</span><span class="s2">"bar"</span><span class="p">,</span> <span class="n">bar</span><span class="p">),</span> <span class="p">(</span><span class="s2">"baz"</span><span class="p">,</span> <span class="n">baz</span><span class="p">)])</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"baz"</span><span class="p">:</span> <span class="n">baz</span><span class="p">,</span> <span class="s2">"bar"</span><span class="p">:</span> <span class="n">bar</span><span class="p">,</span> <span class="s2">"foo"</span><span class="p">:</span> <span class="n">foo</span><span class="p">}</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># Different input types are never considered close.</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">expected</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
<span class="go">AssertionError: Except for scalars, type equality is required, but got</span>
<span class="go"><class 'numpy.ndarray'> and <class 'torch.Tensor'> instead.</span>
<span class="gp">>>> </span><span class="c1"># Scalars of different types are an exception and can be compared with</span>
<span class="gp">>>> </span><span class="c1"># check_dtype=False.</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">check_dtype</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># NaN != NaN by default.</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="nb">float</span><span class="p">(</span><span class="s2">"Nan"</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">expected</span><span class="o">.</span><span class="n">clone</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">)</span>
<span class="go">AssertionError: Tensors are not close!</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">equal_nan</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># If equal_nan=True, the real and imaginary NaN's of complex inputs have to match.</span>
<span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="nb">complex</span><span class="p">(</span><span class="nb">float</span><span class="p">(</span><span class="s2">"NaN"</span><span class="p">),</span> <span class="mi">0</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="nb">complex</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">float</span><span class="p">(</span><span class="s2">"NaN"</span><span class="p">)))</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">equal_nan</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="go">AssertionError: Tensors are not close!</span>
<span class="gp">>>> </span><span class="c1"># If equal_nan="relaxed", however, then complex numbers are treated as NaN if any</span>
<span class="gp">>>> </span><span class="c1"># of the real or imaginary component is NaN.</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">equal_nan</span><span class="o">=</span><span class="s2">"relaxed"</span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">expected</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">actual</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">4.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">])</span>
<span class="gp">>>> </span><span class="c1"># The default mismatch message can be overwritten.</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">msg</span><span class="o">=</span><span class="s2">"Argh, the tensors are not close!"</span><span class="p">)</span>
<span class="go">AssertionError: Argh, the tensors are not close!</span>
<span class="gp">>>> </span><span class="c1"># The error message can also created at runtime by passing a callable.</span>
<span class="gp">>>> </span><span class="k">def</span> <span class="nf">custom_msg</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">diagnostic_info</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="p">(</span>
<span class="gp">... </span> <span class="sa">f</span><span class="s2">"Argh, we found </span><span class="si">{</span><span class="n">diagnostic_info</span><span class="o">.</span><span class="n">total_mismatches</span><span class="si">}</span><span class="s2"> mismatches! "</span>
<span class="gp">... </span> <span class="sa">f</span><span class="s2">"That is </span><span class="si">{</span><span class="n">diagnostic_info</span><span class="o">.</span><span class="n">mismatch_ratio</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">!"</span>
<span class="gp">... </span> <span class="p">)</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_close</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">msg</span><span class="o">=</span><span class="n">custom_msg</span><span class="p">)</span>
<span class="go">AssertionError: Argh, we found 2 mismatches! That is 66.7%!</span>
</pre></div>
</div>
</dd></dl>
</div>
</article>
</div>
<footer>
<div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
<a href="benchmark_utils.html" class="btn btn-neutral float-right" title="Benchmark Utils - torch.utils.benchmark" accesskey="n" rel="next">Next <img src="_static/images/chevron-right-orange.svg" class="next-page"></a>
<a href="storage.html" class="btn btn-neutral" title="torch.Storage" accesskey="p" rel="prev"><img src="_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
</div>
<hr>
<div role="contentinfo">
<p>
© Copyright 2019, Torch Contributors.
</p>
</div>
<div>
Built with <a href="http://sphinx-doc.org/">Sphinx</a> using a <a href="https://github.com/rtfd/sphinx_rtd_theme">theme</a> provided by <a href="https://readthedocs.org">Read the Docs</a>.
</div>
</footer>
</div>
</div>
<div class="pytorch-content-right" id="pytorch-content-right">
<div class="pytorch-right-menu" id="pytorch-right-menu">
<div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
<ul>
<li><a class="reference internal" href="#">torch.testing</a></li>
</ul>
</div>
</div>
</div>
</section>
</div>
<script type="text/javascript" id="documentation_options" data-url_root="./" src="_static/documentation_options.js"></script>
<script src="_static/jquery.js"></script>
<script src="_static/underscore.js"></script>
<script src="_static/doctools.js"></script>
<script src="_static/language_data.js"></script>
<script type="text/javascript" src="_static/js/vendor/popper.min.js"></script>
<script type="text/javascript" src="_static/js/vendor/bootstrap.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/list.js/1.5.0/list.min.js"></script>
<script type="text/javascript" src="_static/js/theme.js"></script>
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
<script script type="text/javascript">
var collapsedSections = ['Notes', 'Language Bindings', 'Libraries', 'Community'];
</script>
<img height="1" width="1" style="border-style:none;" alt="" src="https://www.googleadservices.com/pagead/conversion/795629140/?label=txkmCPmdtosBENSssfsC&guid=ON&script=0"/>
<!-- Begin Footer -->
<div class="container-fluid docs-tutorials-resources" id="docs-tutorials-resources">
<div class="container">
<div class="row">
<div class="col-md-4 text-center">
<h2>Docs</h2>
<p>Access comprehensive developer documentation for PyTorch</p>
<a class="with-right-arrow" href="https://pytorch.org/docs/stable/index.html">View Docs</a>
</div>
<div class="col-md-4 text-center">
<h2>Tutorials</h2>
<p>Get in-depth tutorials for beginners and advanced developers</p>
<a class="with-right-arrow" href="https://pytorch.org/tutorials">View Tutorials</a>
</div>
<div class="col-md-4 text-center">
<h2>Resources</h2>
<p>Find development resources and get your questions answered</p>
<a class="with-right-arrow" href="https://pytorch.org/resources">View Resources</a>
</div>
</div>
</div>
</div>
<footer class="site-footer">
<div class="container footer-container">
<div class="footer-logo-wrapper">
<a href="https://pytorch.org/" class="footer-logo"></a>
</div>
<div class="footer-links-wrapper">
<div class="footer-links-col">
<ul>
<li class="list-title"><a href="https://pytorch.org/">PyTorch</a></li>
<li><a href="https://pytorch.org/get-started">Get Started</a></li>
<li><a href="https://pytorch.org/features">Features</a></li>
<li><a href="https://pytorch.org/ecosystem">Ecosystem</a></li>
<li><a href="https://pytorch.org/blog/">Blog</a></li>
<li><a href="https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md">Contributing</a></li>
</ul>
</div>
<div class="footer-links-col">
<ul>
<li class="list-title"><a href="https://pytorch.org/resources">Resources</a></li>
<li><a href="https://pytorch.org/tutorials">Tutorials</a></li>
<li><a href="https://pytorch.org/docs/stable/index.html">Docs</a></li>
<li><a href="https://discuss.pytorch.org" target="_blank">Discuss</a></li>
<li><a href="https://github.com/pytorch/pytorch/issues" target="_blank">Github Issues</a></li>
<li><a href="https://pytorch.org/assets/brand-guidelines/PyTorch-Brand-Guidelines.pdf" target="_blank">Brand Guidelines</a></li>
</ul>
</div>
<div class="footer-links-col follow-us-col">
<ul>
<li class="list-title">Stay Connected</li>
<li>
<div id="mc_embed_signup">
<form
action="https://twitter.us14.list-manage.com/subscribe/post?u=75419c71fe0a935e53dfa4a3f&id=91d0dccd39"
method="post"
id="mc-embedded-subscribe-form"
name="mc-embedded-subscribe-form"
class="email-subscribe-form validate"
target="_blank"
novalidate>
<div id="mc_embed_signup_scroll" class="email-subscribe-form-fields-wrapper">
<div class="mc-field-group">
<label for="mce-EMAIL" style="display:none;">Email Address</label>
<input type="email" value="" name="EMAIL" class="required email" id="mce-EMAIL" placeholder="Email Address">
</div>
<div id="mce-responses" class="clear">
<div class="response" id="mce-error-response" style="display:none"></div>
<div class="response" id="mce-success-response" style="display:none"></div>
</div> <!-- real people should not fill this in and expect good things - do not remove this or risk form bot signups-->
<div style="position: absolute; left: -5000px;" aria-hidden="true"><input type="text" name="b_75419c71fe0a935e53dfa4a3f_91d0dccd39" tabindex="-1" value=""></div>
<div class="clear">
<input type="submit" value="" name="subscribe" id="mc-embedded-subscribe" class="button email-subscribe-button">
</div>
</div>
</form>
</div>
</li>
</ul>
<div class="footer-social-icons">
<a href="https://www.facebook.com/pytorch" target="_blank" class="facebook"></a>
<a href="https://twitter.com/pytorch" target="_blank" class="twitter"></a>
<a href="https://www.youtube.com/pytorch" target="_blank" class="youtube"></a>
</div>
</div>
</div>
</div>
</footer>
<div class="cookie-banner-wrapper">
<div class="container">
<p class="gdpr-notice">To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: <a href="https://www.facebook.com/policies/cookies/">Cookies Policy</a>.</p>
<img class="close-button" src="_static/images/pytorch-x.svg">
</div>
</div>
<!-- End Footer -->
<!-- Begin Mobile Menu -->
<div class="mobile-main-menu">
<div class="container-fluid">
<div class="container">
<div class="mobile-main-menu-header-container">
<a class="header-logo" href="https://pytorch.org/" aria-label="PyTorch"></a>
<a class="main-menu-close-button" href="#" data-behavior="close-mobile-menu"></a>
</div>
</div>
</div>
<div class="mobile-main-menu-links-container">
<div class="main-menu">
<ul>
<li>
<a href="https://pytorch.org/get-started">Get Started</a>
</li>
<li>
<a href="https://pytorch.org/ecosystem">Ecosystem</a>
</li>
<li>
<a href="https://pytorch.org/mobile">Mobile</a>
</li>
<li>
<a href="https://pytorch.org/hub">PyTorch Hub</a>
</li>
<li>
<a href="https://pytorch.org/blog/">Blog</a>
</li>
<li>
<a href="https://pytorch.org/tutorials">Tutorials</a>
</li>
<li class="resources-mobile-menu-title" class="active">
Docs
</li>
<ul class="resources-mobile-menu-items">
<li>
<a href="https://pytorch.org/docs/stable/index.html">PyTorch</a>
</li>
<li>
<a href="https://pytorch.org/audio/stable/index.html">torchaudio</a>
</li>
<li>
<a href="https://pytorch.org/text/stable/index.html">torchtext</a>
</li>
<li>
<a href="https://pytorch.org/vision/stable/index.html">torchvision</a>
</li>
<li>
<a href="https://pytorch.org/elastic/">TorchElastic</a>
</li>
<li>
<a href="https://pytorch.org/serve/">TorchServe</a>
</li>
<li>
<a href="https://pytorch.org/xla">PyTorch on XLA Devices</a>
</li>
</ul>
<li class="resources-mobile-menu-title">
Resources
</li>
<ul class="resources-mobile-menu-items">
<li>
<a href="https://pytorch.org/resources">Developer Resources</a>
</li>
<li>
<a href="https://pytorch.org/features">About</a>
</li>
<li>
<a href="https://pytorch.org/hub">Models (Beta)</a>
</li>
<li>
<a href="https://pytorch.org/#community-module">Community</a>
</li>
<li>
<a href="https://discuss.pytorch.org/">Forums</a>
</li>
</ul>
<li>
<a href="https://github.com/pytorch/pytorch">Github</a>
</li>
</ul>
</div>
</div>
</div>
<!-- End Mobile Menu -->
<script type="text/javascript" src="_static/js/vendor/anchor.min.js"></script>
<script type="text/javascript">
$(document).ready(function() {
mobileMenu.bind();
mobileTOC.bind();
pytorchAnchors.bind();
sideMenus.bind();
scrollToAnchor.bind();
highlightNavigation.bind();
mainMenuDropdown.bind();
filterTags.bind();
// Add class to links that have code blocks, since we cannot create links in code blocks
$("article.pytorch-article a span.pre").each(function(e) {
$(this).closest("a").addClass("has-code");
});
})
</script>
</body>
</html>