-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathhub.html
1201 lines (998 loc) · 87.6 KB
/
hub.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
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!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.hub — PyTorch 2.1 documentation</title>
<link rel="canonical" href="https://pytorch.org/docs/stable/hub.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="_static/pygments.css" type="text/css" />
<link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="_static/copybutton.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="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="stylesheet" href="_static/sphinx-dropdown.css" type="text/css" />
<link rel="stylesheet" href="_static/panels-bootstrap.min.css" type="text/css" />
<link rel="stylesheet" href="_static/css/jit.css" type="text/css" />
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
<link rel="next" title="TorchScript" href="jit.html" />
<link rel="prev" title="torch.fx" href="fx.html" />
<!-- Google Tag Manager -->
<script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
})(window,document,'script','dataLayer','GTM-T8XT4PS');</script>
<!-- End Google Tag Manager -->
<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/torcharrow">
<span class="dropdown-title">torcharrow</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/data">
<span class="dropdown-title">TorchData</span>
<p></p>
</a>
<a class="doc-dropdown-option nav-dropdown-item" href="https://pytorch.org/torchrec">
<span class="dropdown-title">TorchRec</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/torchx/">
<span class="dropdown-title">TorchX</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/foundation">
<span class="dropdown-title">PyTorch Foundation</span>
<p>Learn about the PyTorch foundation</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/community-stories">
<span class="dropdown-title">Community Stories</span>
<p>Learn how our community solves real, everyday machine learning problems with PyTorch.</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://pytorch.org/events">
<span class="dropdown-title">Events</span>
<p>Find events, webinars, and podcasts</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'>2.1 ▼</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" role="heading"><span class="caption-text">Community</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="community/build_ci_governance.html">PyTorch Governance | Build + CI</a></li>
<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/design.html">PyTorch Design Philosophy</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/governance.html">PyTorch Governance | Mechanics</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/persons_of_interest.html">PyTorch Governance | Maintainers</a></li>
</ul>
<p class="caption" role="heading"><span class="caption-text">Developer Notes</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">CUDA 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/extending.func.html">Extending torch.func with autograd.Function</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/mps.html">MPS backend</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/numerical_accuracy.html">Numerical accuracy</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" role="heading"><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>
<li class="toctree-l1"><a class="reference internal" href="deploy.html">torch::deploy</a></li>
</ul>
<p class="caption" role="heading"><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="amp.html">torch.amp</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="library.html">torch.library</a></li>
<li class="toctree-l1"><a class="reference internal" href="cpu.html">torch.cpu</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="torch_cuda_memory.html">Understanding CUDA Memory Usage</a></li>
<li class="toctree-l1"><a class="reference internal" href="torch_cuda_memory.html#generating-a-snapshot">Generating a Snapshot</a></li>
<li class="toctree-l1"><a class="reference internal" href="torch_cuda_memory.html#using-the-visualizer">Using the visualizer</a></li>
<li class="toctree-l1"><a class="reference internal" href="torch_cuda_memory.html#snapshot-api-reference">Snapshot API Reference</a></li>
<li class="toctree-l1"><a class="reference internal" href="mps.html">torch.mps</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="export.html">torch.export</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.algorithms.join.html">torch.distributed.algorithms.join</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="fsdp.html">torch.distributed.fsdp</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="distributed.tensor.parallel.html">torch.distributed.tensor.parallel</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributed.checkpoint.html">torch.distributed.checkpoint</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="torch.compiler.html">torch.compiler</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="func.html">torch.func</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 current"><a class="current reference internal" href="#">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="monitor.html">torch.monitor</a></li>
<li class="toctree-l1"><a class="reference internal" href="signal.html">torch.signal</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="masked.html">torch.masked</a></li>
<li class="toctree-l1"><a class="reference internal" href="nested.html">torch.nested</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"><a class="reference internal" href="testing.html">torch.testing</a></li>
<li class="toctree-l1"><a class="reference internal" href="utils.html">torch.utils</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="jit_utils.html">torch.utils.jit</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_mod.html">torch.__config__</a></li>
<li class="toctree-l1"><a class="reference internal" href="logging.html">torch._logging</a></li>
</ul>
<p class="caption" role="heading"><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/data">TorchData</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/torchrec">TorchRec</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="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/xla/">PyTorch on XLA Devices</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.hub</li>
<li class="pytorch-breadcrumbs-aside">
<a href="_sources/hub.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">
<!-- Google Tag Manager (noscript) -->
<noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-T8XT4PS"
height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
<!-- End Google Tag Manager (noscript) -->
<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-hub">
<h1>torch.hub<a class="headerlink" href="#torch-hub" title="Permalink to this heading">¶</a></h1>
<p>Pytorch Hub is a pre-trained model repository designed to facilitate research reproducibility.</p>
<div class="section" id="publishing-models">
<h2>Publishing models<a class="headerlink" href="#publishing-models" title="Permalink to this heading">¶</a></h2>
<p>Pytorch Hub supports publishing pre-trained models(model definitions and pre-trained weights)
to a GitHub repository by adding a simple <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> file;</p>
<p><code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> can have multiple entrypoints. Each entrypoint is defined as a python function
(example: a pre-trained model you want to publish).</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">entrypoint_name</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="c1"># args & kwargs are optional, for models which take positional/keyword arguments.</span>
<span class="o">...</span>
</pre></div>
</div>
<div class="section" id="how-to-implement-an-entrypoint">
<h3>How to implement an entrypoint?<a class="headerlink" href="#how-to-implement-an-entrypoint" title="Permalink to this heading">¶</a></h3>
<p>Here is a code snippet specifies an entrypoint for <code class="docutils literal notranslate"><span class="pre">resnet18</span></code> model if we expand
the implementation in <code class="docutils literal notranslate"><span class="pre">pytorch/vision/hubconf.py</span></code>.
In most case importing the right function in <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> is sufficient. Here we
just want to use the expanded version as an example to show how it works.
You can see the full script in
<a class="reference external" href="https://github.com/pytorch/vision/blob/master/hubconf.py">pytorch/vision repo</a></p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">dependencies</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'torch'</span><span class="p">]</span>
<span class="kn">from</span> <span class="nn">torchvision.models.resnet</span> <span class="kn">import</span> <span class="n">resnet18</span> <span class="k">as</span> <span class="n">_resnet18</span>
<span class="c1"># resnet18 is the name of entrypoint</span>
<span class="k">def</span> <span class="nf">resnet18</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="w"> </span><span class="sd">""" # This docstring shows up in hub.help()</span>
<span class="sd"> Resnet18 model</span>
<span class="sd"> pretrained (bool): kwargs, load pretrained weights into the model</span>
<span class="sd"> """</span>
<span class="c1"># Call the model, load pretrained weights</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">_resnet18</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="n">pretrained</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">return</span> <span class="n">model</span>
</pre></div>
</div>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">dependencies</span></code> variable is a <strong>list</strong> of package names required to <strong>load</strong> the model. Note this might
be slightly different from dependencies required for training a model.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">args</span></code> and <code class="docutils literal notranslate"><span class="pre">kwargs</span></code> are passed along to the real callable function.</p></li>
<li><p>Docstring of the function works as a help message. It explains what does the model do and what
are the allowed positional/keyword arguments. It’s highly recommended to add a few examples here.</p></li>
<li><p>Entrypoint function can either return a model(nn.module), or auxiliary tools to make the user workflow smoother, e.g. tokenizers.</p></li>
<li><p>Callables prefixed with underscore are considered as helper functions which won’t show up in <a class="reference internal" href="#torch.hub.list" title="torch.hub.list"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.list()</span></code></a>.</p></li>
<li><p>Pretrained weights can either be stored locally in the GitHub repo, or loadable by
<a class="reference internal" href="#torch.hub.load_state_dict_from_url" title="torch.hub.load_state_dict_from_url"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load_state_dict_from_url()</span></code></a>. If less than 2GB, it’s recommended to attach it to a <a class="reference external" href="https://help.github.com/en/articles/distributing-large-binaries">project release</a>
and use the url from the release.
In the example above <code class="docutils literal notranslate"><span class="pre">torchvision.models.resnet.resnet18</span></code> handles <code class="docutils literal notranslate"><span class="pre">pretrained</span></code>, alternatively you can put the following logic in the entrypoint definition.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">pretrained</span><span class="p">:</span>
<span class="c1"># For checkpoint saved in local GitHub repo, e.g. <RELATIVE_PATH_TO_CHECKPOINT>=weights/save.pth</span>
<span class="n">dirname</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="vm">__file__</span><span class="p">)</span>
<span class="n">checkpoint</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">dirname</span><span class="p">,</span> <span class="o"><</span><span class="n">RELATIVE_PATH_TO_CHECKPOINT</span><span class="o">></span><span class="p">)</span>
<span class="n">state_dict</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">state_dict</span><span class="p">)</span>
<span class="c1"># For checkpoint saved elsewhere</span>
<span class="n">checkpoint</span> <span class="o">=</span> <span class="s1">'https://download.pytorch.org/models/resnet18-5c106cde.pth'</span>
<span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load_state_dict_from_url</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">,</span> <span class="n">progress</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
</pre></div>
</div>
</div>
<div class="section" id="important-notice">
<h3>Important Notice<a class="headerlink" href="#important-notice" title="Permalink to this heading">¶</a></h3>
<ul class="simple">
<li><p>The published models should be at least in a branch/tag. It can’t be a random commit.</p></li>
</ul>
</div>
</div>
<div class="section" id="loading-models-from-hub">
<h2>Loading models from Hub<a class="headerlink" href="#loading-models-from-hub" title="Permalink to this heading">¶</a></h2>
<p>Pytorch Hub provides convenient APIs to explore all available models in hub
through <a class="reference internal" href="#torch.hub.list" title="torch.hub.list"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.list()</span></code></a>, show docstring and examples through
<a class="reference internal" href="#torch.hub.help" title="torch.hub.help"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.help()</span></code></a> and load the pre-trained models using
<a class="reference internal" href="#torch.hub.load" title="torch.hub.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load()</span></code></a>.</p>
<span class="target" id="module-torch.hub"></span><dl class="py function">
<dt class="sig sig-object py" id="torch.hub.list">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">github</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#list"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.list" title="Permalink to this definition">¶</a></dt>
<dd><p>List all callable entrypoints available in the repo specified by <code class="docutils literal notranslate"><span class="pre">github</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>github</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – a string with format “repo_owner/repo_name[:ref]” with an optional
ref (tag or branch). If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified, the default branch is assumed to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if
it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
Example: ‘pytorch/vision:0.10’</p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to discard the existing cache and force a fresh download.
Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the branch or commit
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">"check"</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">"check"</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">"check"</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">"check"</span></code> in v2.0.</p>
</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The available callables entrypoint</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)">list</a></p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">entrypoints</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">list</span><span class="p">(</span><span class="s1">'pytorch/vision'</span><span class="p">,</span> <span class="n">force_reload</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.help">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">help</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">github</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#help"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.help" title="Permalink to this definition">¶</a></dt>
<dd><p>Show the docstring of entrypoint <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>github</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – a string with format <repo_owner/repo_name[:ref]> with an optional
ref (a tag or a branch). If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified, the default branch is assumed
to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
Example: ‘pytorch/vision:0.10’</p></li>
<li><p><strong>model</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – a string of entrypoint name defined in repo’s <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code></p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to discard the existing cache and force a fresh download.
Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the ref
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">"check"</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">"check"</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">"check"</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">"check"</span></code> in v2.0.</p>
</p></li>
</ul>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">help</span><span class="p">(</span><span class="s1">'pytorch/vision'</span><span class="p">,</span> <span class="s1">'resnet18'</span><span class="p">,</span> <span class="n">force_reload</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.load">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">repo_or_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <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="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'github'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</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">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</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="reference internal" href="_modules/torch/hub.html#load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.load" title="Permalink to this definition">¶</a></dt>
<dd><p>Load a model from a github repo or a local directory.</p>
<p>Note: Loading a model is the typical use case, but this can also be used to
for loading other objects such as tokenizers, loss functions, etc.</p>
<p>If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘github’, <code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is expected to be
of the form <code class="docutils literal notranslate"><span class="pre">repo_owner/repo_name[:ref]</span></code> with an optional
ref (a tag or a branch).</p>
<p>If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘local’, <code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is expected to be a
path to a local directory.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>repo_or_dir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘github’,
this should correspond to a github repo with format <code class="docutils literal notranslate"><span class="pre">repo_owner/repo_name[:ref]</span></code> with
an optional ref (tag or branch), for example ‘pytorch/vision:0.10’. If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified,
the default branch is assumed to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘local’ then it should be a path to a local directory.</p></li>
<li><p><strong>model</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – the name of a callable (entrypoint) defined in the
repo/dir’s <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code>.</p></li>
<li><p><strong>*args</strong> (<em>optional</em>) – the corresponding args for callable <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p></li>
<li><p><strong>source</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – ‘github’ or ‘local’. Specifies how
<code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is to be interpreted. Default is ‘github’.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">"check"</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">"check"</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">"check"</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">"check"</span></code> in v2.0.</p>
</p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to force a fresh download of
the github repo unconditionally. Does not have any effect if
<code class="docutils literal notranslate"><span class="pre">source</span> <span class="pre">=</span> <span class="pre">'local'</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>verbose</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – If <code class="docutils literal notranslate"><span class="pre">False</span></code>, mute messages about hitting
local caches. Note that the message about first download cannot be
muted. Does not have any effect if <code class="docutils literal notranslate"><span class="pre">source</span> <span class="pre">=</span> <span class="pre">'local'</span></code>.
Default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the branch or commit
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>**kwargs</strong> (<em>optional</em>) – the corresponding kwargs for callable <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The output of the <code class="docutils literal notranslate"><span class="pre">model</span></code> callable when called with the given
<code class="docutils literal notranslate"><span class="pre">*args</span></code> and <code class="docutils literal notranslate"><span class="pre">**kwargs</span></code>.</p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># from a github repo</span>
<span class="gp">>>> </span><span class="n">repo</span> <span class="o">=</span> <span class="s1">'pytorch/vision'</span>
<span class="gp">>>> </span><span class="n">model</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">repo</span><span class="p">,</span> <span class="s1">'resnet50'</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="s1">'ResNet50_Weights.IMAGENET1K_V1'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># from a local directory</span>
<span class="gp">>>> </span><span class="n">path</span> <span class="o">=</span> <span class="s1">'/some/local/path/pytorch/vision'</span>
<span class="gp">>>> </span><span class="n">model</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">'resnet50'</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="s1">'ResNet50_Weights.DEFAULT'</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.download_url_to_file">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">download_url_to_file</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">url</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hash_prefix</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">progress</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#download_url_to_file"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.download_url_to_file" title="Permalink to this definition">¶</a></dt>
<dd><p>Download object at the given URL to a local path.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>url</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – URL of the object to download</p></li>
<li><p><strong>dst</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Full path where object will be saved, e.g. <code class="docutils literal notranslate"><span class="pre">/tmp/temporary_file</span></code></p></li>
<li><p><strong>hash_prefix</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – If not None, the SHA256 downloaded file should start with <code class="docutils literal notranslate"><span class="pre">hash_prefix</span></code>.
Default: None</p></li>
<li><p><strong>progress</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – whether or not to display a progress bar to stderr
Default: True</p></li>
</ul>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">download_url_to_file</span><span class="p">(</span><span class="s1">'https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth'</span><span class="p">,</span> <span class="s1">'/tmp/temporary_file'</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.load_state_dict_from_url">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">load_state_dict_from_url</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">url</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_dir</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">map_location</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">progress</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_hash</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_name</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">weights_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#load_state_dict_from_url"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.load_state_dict_from_url" title="Permalink to this definition">¶</a></dt>
<dd><p>Loads the Torch serialized object at the given URL.</p>
<p>If downloaded file is a zip file, it will be automatically
decompressed.</p>
<p>If the object is already present in <cite>model_dir</cite>, it’s deserialized and
returned.
The default value of <code class="docutils literal notranslate"><span class="pre">model_dir</span></code> is <code class="docutils literal notranslate"><span class="pre"><hub_dir>/checkpoints</span></code> where
<code class="docutils literal notranslate"><span class="pre">hub_dir</span></code> is the directory returned by <a class="reference internal" href="#torch.hub.get_dir" title="torch.hub.get_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">get_dir()</span></code></a>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>url</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – URL of the object to download</p></li>
<li><p><strong>model_dir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – directory in which to save the object</p></li>
<li><p><strong>map_location</strong> (<em>optional</em>) – a function or a dict specifying how to remap storage locations (see torch.load)</p></li>
<li><p><strong>progress</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – whether or not to display a progress bar to stderr.
Default: True</p></li>
<li><p><strong>check_hash</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, the filename part of the URL should follow the naming convention
<code class="docutils literal notranslate"><span class="pre">filename-<sha256>.ext</span></code> where <code class="docutils literal notranslate"><span class="pre"><sha256></span></code> is the first eight or more
digits of the SHA256 hash of the contents of the file. The hash is used to
ensure unique names and to verify the contents of the file.
Default: False</p></li>
<li><p><strong>file_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – name for the downloaded file. Filename from <code class="docutils literal notranslate"><span class="pre">url</span></code> will be used if not set.</p></li>
<li><p><strong>weights_only</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, only weights will be loaded and no complex pickled objects.
Recommended for untrusted sources. See <a class="reference internal" href="generated/torch.load.html#torch.load" title="torch.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">load()</span></code></a> for more details.</p></li>
</ul>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><em>Dict</em></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><em>Any</em></a>]</p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">state_dict</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load_state_dict_from_url</span><span class="p">(</span><span class="s1">'https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth'</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<div class="section" id="running-a-loaded-model">
<h3>Running a loaded model:<a class="headerlink" href="#running-a-loaded-model" title="Permalink to this heading">¶</a></h3>
<p>Note that <code class="docutils literal notranslate"><span class="pre">*args</span></code> and <code class="docutils literal notranslate"><span class="pre">**kwargs</span></code> in <a class="reference internal" href="#torch.hub.load" title="torch.hub.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load()</span></code></a> are used to
<strong>instantiate</strong> a model. After you have loaded a model, how can you find out
what you can do with the model?
A suggested workflow is</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">dir(model)</span></code> to see all available methods of the model.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">help(model.foo)</span></code> to check what arguments <code class="docutils literal notranslate"><span class="pre">model.foo</span></code> takes to run</p></li>
</ul>
<p>To help users explore without referring to documentation back and forth, we strongly
recommend repo owners make function help messages clear and succinct. It’s also helpful
to include a minimal working example.</p>
</div>
<div class="section" id="where-are-my-downloaded-models-saved">
<h3>Where are my downloaded models saved?<a class="headerlink" href="#where-are-my-downloaded-models-saved" title="Permalink to this heading">¶</a></h3>
<p>The locations are used in the order of</p>
<ul class="simple">
<li><p>Calling <code class="docutils literal notranslate"><span class="pre">hub.set_dir(<PATH_TO_HUB_DIR>)</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$TORCH_HOME/hub</span></code>, if environment variable <code class="docutils literal notranslate"><span class="pre">TORCH_HOME</span></code> is set.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME/torch/hub</span></code>, if environment variable <code class="docutils literal notranslate"><span class="pre">XDG_CACHE_HOME</span></code> is set.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">~/.cache/torch/hub</span></code></p></li>
</ul>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.get_dir">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">get_dir</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#get_dir"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.get_dir" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the Torch Hub cache directory used for storing downloaded models & weights.</p>
<p>If <a class="reference internal" href="#torch.hub.set_dir" title="torch.hub.set_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">set_dir()</span></code></a> is not called, default path is <code class="docutils literal notranslate"><span class="pre">$TORCH_HOME/hub</span></code> where
environment variable <code class="docutils literal notranslate"><span class="pre">$TORCH_HOME</span></code> defaults to <code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME/torch</span></code>.
<code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME</span></code> follows the X Design Group specification of the Linux
filesystem layout, with a default value <code class="docutils literal notranslate"><span class="pre">~/.cache</span></code> if the environment
variable is not set.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.set_dir">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">set_dir</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/hub.html#set_dir"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.set_dir" title="Permalink to this definition">¶</a></dt>
<dd><p>Optionally set the Torch Hub directory used to save downloaded models & weights.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>d</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – path to a local folder to save downloaded models & weights.</p>
</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="caching-logic">
<h3>Caching logic<a class="headerlink" href="#caching-logic" title="Permalink to this heading">¶</a></h3>
<p>By default, we don’t clean up files after loading it. Hub uses the cache by default if it already exists in the
directory returned by <a class="reference internal" href="#torch.hub.get_dir" title="torch.hub.get_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">get_dir()</span></code></a>.</p>
<p>Users can force a reload by calling <code class="docutils literal notranslate"><span class="pre">hub.load(...,</span> <span class="pre">force_reload=True)</span></code>. This will delete
the existing GitHub folder and downloaded weights, reinitialize a fresh download. This is useful
when updates are published to the same branch, users can keep up with the latest release.</p>
</div>
<div class="section" id="known-limitations">
<h3>Known limitations:<a class="headerlink" href="#known-limitations" title="Permalink to this heading">¶</a></h3>
<p>Torch hub works by importing the package as if it was installed. There are some side effects
introduced by importing in Python. For example, you can see new items in Python caches
<code class="docutils literal notranslate"><span class="pre">sys.modules</span></code> and <code class="docutils literal notranslate"><span class="pre">sys.path_importer_cache</span></code> which is normal Python behavior.
This also means that you may have import errors when importing different models
from different repos, if the repos have the same sub-package names (typically, a
<code class="docutils literal notranslate"><span class="pre">model</span></code> subpackage). A workaround for these kinds of import errors is to
remove the offending sub-package from the <code class="docutils literal notranslate"><span class="pre">sys.modules</span></code> dict; more details can
be found in <a class="reference external" href="https://github.com/pytorch/hub/issues/243#issuecomment-942403391">this GitHub issue</a>.</p>
<p>A known limitation that is worth mentioning here: users <strong>CANNOT</strong> load two different branches of
the same repo in the <strong>same python process</strong>. It’s just like installing two packages with the
same name in Python, which is not good. Cache might join the party and give you surprises if you
actually try that. Of course it’s totally fine to load them in separate processes.</p>
</div>
</div>
</div>
</article>
</div>
<footer>
<div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
<a href="jit.html" class="btn btn-neutral float-right" title="TorchScript" accesskey="n" rel="next">Next <img src="_static/images/chevron-right-orange.svg" class="next-page"></a>
<a href="fx.html" class="btn btn-neutral" title="torch.fx" accesskey="p" rel="prev"><img src="_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
</div>
<hr>
<div role="contentinfo">
<p>
© Copyright 2023, PyTorch 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>
<script>
var match = window.location.href.match(/\/_[a-zA-Z0-9_]*.html|_dynamo/gi);
var url = window.location.href.lastIndexOf(match[match.length-1]);
if (url)
{
var div = '<div class="admonition note"><p class="admonition-title">Note</p><p><i class="fa fa-exclamation-circle" aria-hidden="true"> </i> This page describes an internal API which is not intended to be used outside of the PyTorch codebase and can be modified or removed without notice.</p></div>'
document.getElementById("pytorch-article").insertAdjacentHTML('afterBegin', div)
}
</script>
</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.hub</a><ul>
<li><a class="reference internal" href="#publishing-models">Publishing models</a><ul>
<li><a class="reference internal" href="#how-to-implement-an-entrypoint">How to implement an entrypoint?</a></li>
<li><a class="reference internal" href="#important-notice">Important Notice</a></li>
</ul>
</li>
<li><a class="reference internal" href="#loading-models-from-hub">Loading models from Hub</a><ul>
<li><a class="reference internal" href="#torch.hub.list"><code class="docutils literal notranslate"><span class="pre">list()</span></code></a></li>
<li><a class="reference internal" href="#torch.hub.help"><code class="docutils literal notranslate"><span class="pre">help()</span></code></a></li>
<li><a class="reference internal" href="#torch.hub.load"><code class="docutils literal notranslate"><span class="pre">load()</span></code></a></li>
<li><a class="reference internal" href="#torch.hub.download_url_to_file"><code class="docutils literal notranslate"><span class="pre">download_url_to_file()</span></code></a></li>
<li><a class="reference internal" href="#torch.hub.load_state_dict_from_url"><code class="docutils literal notranslate"><span class="pre">load_state_dict_from_url()</span></code></a></li>
<li><a class="reference internal" href="#running-a-loaded-model">Running a loaded model:</a></li>
<li><a class="reference internal" href="#where-are-my-downloaded-models-saved">Where are my downloaded models saved?</a><ul>
<li><a class="reference internal" href="#torch.hub.get_dir"><code class="docutils literal notranslate"><span class="pre">get_dir()</span></code></a></li>
<li><a class="reference internal" href="#torch.hub.set_dir"><code class="docutils literal notranslate"><span class="pre">set_dir()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#caching-logic">Caching logic</a></li>
<li><a class="reference internal" href="#known-limitations">Known limitations:</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</section>
</div>
<script type="text/javascript" id="documentation_options" data-url_root="./" src="_static/documentation_options.js"></script>
<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
<script src="_static/jquery.js"></script>
<script src="_static/underscore.js"></script>
<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
<script src="_static/doctools.js"></script>
<script src="_static/sphinx_highlight.js"></script>
<script src="_static/clipboard.min.js"></script>
<script src="_static/copybutton.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 = ['Developer 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>