Anurag1734/cuda-error-resolution-analysis
07
1[2 {3 "post_stream": {4 "posts": [5 {6 "id": 222226,7 "name": "oasjd7",8 "username": "oasjd7",9 "avatar_template": "/user_avatar/discuss.pytorch.org/oasjd7/{size}/5053_2.png",10 "created_at": "2020-08-19T10:50:55.749Z",11 "cooked": "<pre><code class=\"lang-auto\">total_loss += loss(A, B.detach())\ntotal_loss += loss(B, A.detach())\ntotal_loss.backward()\n</code></pre>\n<p>Hi, all</p>\n<p>If I call <code>B.detach()</code> in the front, B cannot be trained after this code?</p>",12 "post_number": 1,13 "post_type": 1,14 "posts_count": 2,15 "updated_at": "2020-08-19T10:50:55.749Z",16 "reply_count": 0,17 "reply_to_post_number": null,18 "quote_count": 0,19 "incoming_link_count": 5,20 "reads": 11,21 "readers_count": 10,22 "score": 27.2,23 "yours": false,24 "topic_id": 93358,25 "topic_slug": "usage-of-detach",26 "display_username": "oasjd7",27 "primary_group_name": null,28 "flair_name": null,29 "flair_url": null,30 "flair_bg_color": null,31 "flair_color": null,32 "flair_group_id": null,33 "badges_granted": [],34 "version": 1,35 "can_edit": false,36 "can_delete": false,37 "can_recover": false,38 "can_see_hidden_post": false,39 "can_wiki": false,40 "read": true,41 "user_title": null,42 "bookmarked": false,43 "actions_summary": [],44 "moderator": false,45 "admin": false,46 "staff": false,47 "user_id": 8236,48 "hidden": false,49 "trust_level": 1,50 "deleted_at": null,51 "user_deleted": false,52 "edit_reason": null,53 "can_view_edit_history": true,54 "wiki": false,55 "post_url": "/t/usage-of-detach/93358/1",56 "can_accept_answer": false,57 "can_unaccept_answer": false,58 "accepted_answer": false,59 "topic_accepted_answer": null,60 "can_vote": false61 },62 {63 "id": 222331,64 "name": "Alban D",65 "username": "albanD",66 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png",67 "created_at": "2020-08-19T16:14:50.295Z",68 "cooked": "<p>Hi,</p>\n<p>What do you mean by “in the front” ?</p>",69 "post_number": 2,70 "post_type": 1,71 "posts_count": 2,72 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"participant_count": 2,444 "show_read_indicator": false,445 "thumbnails": null,446 "slow_mode_enabled_until": null,447 "can_vote": false,448 "vote_count": 0,449 "user_voted": false,450 "discourse_zendesk_plugin_zendesk_id": null,451 "discourse_zendesk_plugin_zendesk_url": "https://your-url.zendesk.com/agent/tickets/",452 "details": {453 "can_edit": false,454 "notification_level": 1,455 "participants": [456 {457 "id": 211,458 "username": "albanD",459 "name": "Alban D",460 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png",461 "post_count": 1,462 "primary_group_name": null,463 "flair_name": null,464 "flair_url": null,465 "flair_color": null,466 "flair_bg_color": null,467 "flair_group_id": null,468 "admin": true,469 "moderator": true,470 "trust_level": 4471 },472 {473 "id": 8236,474 "username": "oasjd7",475 "name": "oasjd7",476 "avatar_template": "/user_avatar/discuss.pytorch.org/oasjd7/{size}/5053_2.png",477 "post_count": 1,478 "primary_group_name": null,479 "flair_name": null,480 "flair_url": null,481 "flair_color": null,482 "flair_bg_color": null,483 "flair_group_id": null,484 "trust_level": 1485 }486 ],487 "created_by": {488 "id": 8236,489 "username": "oasjd7",490 "name": "oasjd7",491 "avatar_template": "/user_avatar/discuss.pytorch.org/oasjd7/{size}/5053_2.png"492 },493 "last_poster": {494 "id": 211,495 "username": "albanD",496 "name": "Alban D",497 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png"498 }499 },500 "bookmarks": []501 },502 {503 "post_stream": {504 "posts": [505 {506 "id": 222278,507 "name": "Adam Ryczkowski",508 "username": "adamr",509 "avatar_template": "/user_avatar/discuss.pytorch.org/adamr/{size}/27859_2.png",510 "created_at": "2020-08-19T13:34:41.261Z",511 "cooked": "<p>I understand that the intended usage of the <code>conv2d</code> is to make it act on 4D input vectors and kernels, the docs never specifically stated that you can’t use it with higher dimensions.</p>\n<p>I tried, for fun, testing what does <code>conv2d</code> does for 5D vectors. First I tried to try the simplest no-op case, that should just return multi-dimensional vector of size 1:</p>\n<pre><code class=\"lang-python\">>>> import torch\n>>> torch.nn.functional.conv2d(torch.ones(1,1,1,1), torch.ones(1,1,1,1))\ntensor([[[[1.]]]])\n>>> torch.nn.functional.conv2d(torch.ones(1,1,1,1,1), torch.ones(1,1,1,1,1))\nRuntimeError: expected stride to be a single integer value or a list of 3 values to match the convolution dimensions, but got stride=[1, 1]\n</code></pre>\n<p>I’ve got the error message asking me to put the correct (three) dimensions on the stride, padding, dilation and… output_padding.</p>\n<pre><code class=\"lang-python\">>>> torch.nn.functional.conv2d(torch.ones(1,1,1,1,1), torch.ones(1,1,1,1,1), stride=(1,1,1), padding=(0,0,0), dilation=(1,1,1), output_padding=(0,0,0))\nTypeError: conv2d() got an unexpected keyword argument 'output_padding'\n</code></pre>\n<p>Is it the pytorch bug? Or did I miss the limitation that the conv2d can only act on 4D vectors - if so, why the code does not check for it <code>assert len(input.shape)==4</code> when it already checks for so many errors?</p>",512 "post_number": 1,513 "post_type": 1,514 "posts_count": 2,515 "updated_at": "2020-08-19T13:37:17.298Z",516 "reply_count": 0,517 "reply_to_post_number": null,518 "quote_count": 0,519 "incoming_link_count": 716,520 "reads": 27,521 "readers_count": 26,522 "score": 3585.4,523 "yours": false,524 "topic_id": 93371,525 "topic_slug": "torch-nn-functional-conv2d-on-5d-vectors",526 "display_username": "Adam Ryczkowski",527 "primary_group_name": null,528 "flair_name": null,529 "flair_url": null,530 "flair_bg_color": null,531 "flair_color": null,532 "flair_group_id": null,533 "badges_granted": [],534 "version": 2,535 "can_edit": false,536 "can_delete": false,537 "can_recover": false,538 "can_see_hidden_post": false,539 "can_wiki": false,540 "read": true,541 "user_title": null,542 "bookmarked": false,543 "actions_summary": [],544 "moderator": false,545 "admin": false,546 "staff": false,547 "user_id": 35594,548 "hidden": false,549 "trust_level": 1,550 "deleted_at": null,551 "user_deleted": false,552 "edit_reason": null,553 "can_view_edit_history": true,554 "wiki": false,555 "post_url": "/t/torch-nn-functional-conv2d-on-5d-vectors/93371/1",556 "can_accept_answer": false,557 "can_unaccept_answer": false,558 "accepted_answer": false,559 "topic_accepted_answer": null,560 "can_vote": false561 },562 {563 "id": 222329,564 "name": "Alban D",565 "username": "albanD",566 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png",567 "created_at": "2020-08-19T16:09:56.942Z",568 "cooked": "<p>Hi,</p>\n<p>Yes, conv2d can only work with 4D inputs. You can use conv3d to work with 5D.<br>\nAnd we are definitely missing some error checking here to make sure the user is not providing wrong arguments. Could you open an issue on github about that please?</p>",569 "post_number": 2,570 "post_type": 1,571 "posts_count": 2,572 "updated_at": "2020-08-19T16:09:56.942Z",573 "reply_count": 0,574 "reply_to_post_number": null,575 "quote_count": 0,576 "incoming_link_count": 4,577 "reads": 25,578 "readers_count": 24,579 "score": 25.0,580 "yours": false,581 "topic_id": 93371,582 "topic_slug": "torch-nn-functional-conv2d-on-5d-vectors",583 "display_username": "Alban D",584 "primary_group_name": null,585 "flair_name": null,586 "flair_url": null,587 "flair_bg_color": null,588 "flair_color": null,589 "flair_group_id": null,590 "badges_granted": [],591 "version": 1,592 "can_edit": false,593 "can_delete": false,594 "can_recover": false,595 "can_see_hidden_post": false,596 "can_wiki": false,597 "read": true,598 "user_title": "",599 "bookmarked": false,600 "actions_summary": [],601 "moderator": true,602 "admin": true,603 "staff": true,604 "user_id": 211,605 "hidden": false,606 "trust_level": 4,607 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"/user_avatar/discuss.pytorch.org/adamr/{size}/27859_2.png"1007 },1008 "last_poster": {1009 "id": 211,1010 "username": "albanD",1011 "name": "Alban D",1012 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png"1013 }1014 },1015 "bookmarks": []1016 },1017 {1018 "post_stream": {1019 "posts": [1020 {1021 "id": 222310,1022 "name": "Had",1023 "username": "hadaev8",1024 "avatar_template": "/user_avatar/discuss.pytorch.org/hadaev8/{size}/16280_2.png",1025 "created_at": "2020-08-19T15:14:27.650Z",1026 "cooked": "<p>Does pytorch or cuda have any specific optimization or something?</p>",1027 "post_number": 1,1028 "post_type": 1,1029 "posts_count": 2,1030 "updated_at": "2020-08-19T15:14:27.650Z",1031 "reply_count": 0,1032 "reply_to_post_number": null,1033 "quote_count": 0,1034 "incoming_link_count": 519,1035 "reads": 34,1036 "readers_count": 33,1037 "score": 2601.8,1038 "yours": false,1039 "topic_id": 93381,1040 "topic_slug": 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"can_vote": false1076 },1077 {1078 "id": 222326,1079 "name": "Alban D",1080 "username": "albanD",1081 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png",1082 "created_at": "2020-08-19T16:05:21.405Z",1083 "cooked": "<p>Hi,</p>\n<p>No it is not mandatory.<br>\nAnd power of 2 are not particularly important either.<br>\nMaybe powers of 32 that are the size of the streaming multiprocessors? But even that depends a lot on how the cuda kernel is implemented and, in general, won’t lead to any significant difference.</p>",1084 "post_number": 2,1085 "post_type": 1,1086 "posts_count": 2,1087 "updated_at": "2020-10-19T15:49:24.529Z",1088 "reply_count": 0,1089 "reply_to_post_number": null,1090 "quote_count": 0,1091 "incoming_link_count": 11,1092 "reads": 34,1093 "readers_count": 33,1094 "score": 61.8,1095 "yours": false,1096 "topic_id": 93381,1097 "topic_slug": "is-it-mandatory-to-have-batch-size-power-of-2-on-gpu",1098 "display_username": "Alban D",1099 "primary_group_name": null,1100 "flair_name": null,1101 "flair_url": null,1102 "flair_bg_color": null,1103 "flair_color": null,1104 "flair_group_id": null,1105 "badges_granted": [],1106 "version": 1,1107 "can_edit": false,1108 "can_delete": false,1109 "can_recover": false,1110 "can_see_hidden_post": false,1111 "can_wiki": false,1112 "read": true,1113 "user_title": "",1114 "bookmarked": false,1115 "actions_summary": [],1116 "moderator": true,1117 "admin": true,1118 "staff": true,1119 "user_id": 211,1120 "hidden": false,1121 "trust_level": 4,1122 "deleted_at": null,1123 "user_deleted": false,1124 "edit_reason": null,1125 "can_view_edit_history": true,1126 "wiki": false,1127 "post_url": "/t/is-it-mandatory-to-have-batch-size-power-of-2-on-gpu/93381/2",1128 "can_accept_answer": false,1129 "can_unaccept_answer": false,1130 "accepted_answer": true,1131 "topic_accepted_answer": true1132 }1133 ],1134 "stream": [1135 222310,1136 2223261137 ]1138 },1139 "timeline_lookup": [1140 [1141 1,1142 18931143 ]1144 ],1145 "suggested_topics": [1146 {1147 "fancy_title": "How to add value to tensor multiple times by index",1148 "id": 212382,1149 "title": "How to add value to tensor multiple times by index",1150 "slug": "how-to-add-value-to-tensor-multiple-times-by-index",1151 "posts_count": 3,1152 "reply_count": 0,1153 "highest_post_number": 3,1154 "image_url": null,1155 "created_at": "2024-10-31T20:08:52.361Z",1156 "last_posted_at": "2024-11-06T07:14:05.689Z",1157 "bumped": true,1158 "bumped_at": "2024-11-06T07:14:05.689Z",1159 "archetype": "regular",1160 "unseen": false,1161 "pinned": false,1162 "unpinned": null,1163 "visible": true,1164 "closed": false,1165 "archived": false,1166 "bookmarked": null,1167 "liked": null,1168 "tags_descriptions": {},1169 "like_count": 1,1170 "views": 181,1171 "category_id": 1,1172 "featured_link": null,1173 "has_accepted_answer": false,1174 "posters": [1175 {1176 "extras": "latest",1177 "description": "Original Poster, Most Recent Poster",1178 "user": {1179 "id": 80623,1180 "username": "dronnet1",1181 "name": "Андрей Медведев",1182 "avatar_template": "/user_avatar/discuss.pytorch.org/dronnet1/{size}/73708_2.png",1183 "trust_level": 11184 }1185 },1186 {1187 "extras": null,1188 "description": "Frequent Poster",1189 "user": {1190 "id": 72430,1191 "username": "Eduardo_Lawson",1192 "name": "Eduardo Lawson da Silva",1193 "avatar_template": "/user_avatar/discuss.pytorch.org/eduardo_lawson/{size}/66899_2.png",1194 "trust_level": 21195 }1196 }1197 ]1198 },1199 {1200 "fancy_title": "From RAM to GRAM",