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Anurag1734/cuda-error-resolution-analysis

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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 359537,7          "name": "Nosin Ibna Mahbub",8          "username": "Nosin_Ibna_Mahbub",9          "avatar_template": "/user_avatar/discuss.pytorch.org/nosin_ibna_mahbub/{size}/44733_2.png",10          "created_at": "2022-08-02T13:02:17.844Z",11          "cooked": "<p>Hello, I am trying to segment medical image and i need help on creating a DataLoader to take into a CNN .mat images. My main image and mask are saved in a same mat file. So, I need help to create custom dataloader to read the main image and mask from the same mat file. Thank you</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 4,15          "updated_at": "2022-08-02T13:02:17.844Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 241,20          "reads": 9,21          "readers_count": 8,22          "score": 1196.8,23          "yours": false,24          "topic_id": 158129,25          "topic_slug": "custom-dataloader-using-mat-file",26          "display_username": "Nosin Ibna Mahbub",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": 58192,48          "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/custom-dataloader-using-mat-file/158129/1",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": 359547,64          "name": "Kevin T",65          "username": "nivek",66          "avatar_template": "/user_avatar/discuss.pytorch.org/nivek/{size}/39672_2.png",67          "created_at": "2022-08-02T13:57:54.904Z",68          "cooked": "<p>Hi, please have a look at our <a href=\"https://pytorch.org/tutorials/beginner/basics/data_tutorial.html\" rel=\"noopener nofollow ugc\">tutorial</a> and let us know what you have tried.</p>",69          "post_number": 2,70          "post_type": 1,71          "posts_count": 4,72          "updated_at": "2022-08-02T13:57:54.904Z",73          "reply_count": 1,74          "reply_to_post_number": null,75          "quote_count": 0,76          "incoming_link_count": 8,77          "reads": 7,78          "readers_count": 6,79          "score": 46.4,80          "yours": false,81          "topic_id": 158129,82          "topic_slug": "custom-dataloader-using-mat-file",83          "display_username": "Kevin T",84          "primary_group_name": null,85          "flair_name": null,86          "flair_url": null,87          "flair_bg_color": null,88          "flair_color": null,89          "flair_group_id": null,90          "badges_granted": [],91          "version": 1,92          "can_edit": false,93          "can_delete": false,94          "can_recover": false,95          "can_see_hidden_post": false,96          "can_wiki": false,97          "link_counts": [98            {99              "url": "https://pytorch.org/tutorials/beginner/basics/data_tutorial.html",100              "internal": false,101              "reflection": false,102              "title": "Datasets & DataLoaders — PyTorch Tutorials 1.12.0+cu102 documentation",103              "clicks": 49104            }105          ],106          "read": true,107          "user_title": "",108          "bookmarked": false,109          "actions_summary": [],110          "moderator": false,111          "admin": false,112          "staff": false,113          "user_id": 46614,114          "hidden": false,115          "trust_level": 2,116          "deleted_at": null,117          "user_deleted": false,118          "edit_reason": null,119          "can_view_edit_history": true,120          "wiki": false,121          "post_url": "/t/custom-dataloader-using-mat-file/158129/2",122          "can_accept_answer": false,123          "can_unaccept_answer": false,124          "accepted_answer": false,125          "topic_accepted_answer": null126        },127        {128          "id": 359585,129          "name": "Nosin Ibna Mahbub",130          "username": "Nosin_Ibna_Mahbub",131          "avatar_template": "/user_avatar/discuss.pytorch.org/nosin_ibna_mahbub/{size}/44733_2.png",132          "created_at": "2022-08-02T16:15:39.049Z",133          "cooked": "<p>Thanks for your reply.<br>\nI have around 4000 mat files. Each mat file contains main image and mask which is shown in the following image. I have to make custom dataloader for this dataset to train the model.<br>\n<div class=\"lightbox-wrapper\"><a class=\"lightbox\" href=\"https://discuss.pytorch.org/uploads/default/original/3X/2/7/27cc7a4afbe6786f9be1fb619bbbaf782708001d.jpeg\" data-download-href=\"https://discuss.pytorch.org/uploads/default/27cc7a4afbe6786f9be1fb619bbbaf782708001d\" title=\"mat_file_read\"><img src=\"https://discuss.pytorch.org/uploads/default/optimized/3X/2/7/27cc7a4afbe6786f9be1fb619bbbaf782708001d_2_690x314.jpeg\" alt=\"mat_file_read\" data-base62-sha1=\"5G4Ic3r3tOG7otElj3kvuzr1TwV\" width=\"690\" height=\"314\" srcset=\"https://discuss.pytorch.org/uploads/default/optimized/3X/2/7/27cc7a4afbe6786f9be1fb619bbbaf782708001d_2_690x314.jpeg, https://discuss.pytorch.org/uploads/default/original/3X/2/7/27cc7a4afbe6786f9be1fb619bbbaf782708001d.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/2/7/27cc7a4afbe6786f9be1fb619bbbaf782708001d.jpeg 2x\" data-dominant-color=\"F5F5F5\"><div class=\"meta\"><svg class=\"fa d-icon d-icon-far-image svg-icon\" aria-hidden=\"true\"><use href=\"#far-image\"></use></svg><span class=\"filename\">mat_file_read</span><span class=\"informations\">724×330 50.8 KB</span><svg class=\"fa d-icon d-icon-discourse-expand svg-icon\" aria-hidden=\"true\"><use href=\"#discourse-expand\"></use></svg></div></a></div></p>",134          "post_number": 4,135          "post_type": 1,136          "posts_count": 4,137          "updated_at": "2022-08-02T16:15:39.049Z",138          "reply_count": 1,139          "reply_to_post_number": 2,140          "quote_count": 0,141          "incoming_link_count": 14,142          "reads": 7,143          "readers_count": 6,144          "score": 76.4,145          "yours": false,146          "topic_id": 158129,147          "topic_slug": "custom-dataloader-using-mat-file",148          "display_username": "Nosin Ibna Mahbub",149          "primary_group_name": null,150          "flair_name": null,151          "flair_url": 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like the right approach and you could use e.g. <a href=\"https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html\"><code>scipy.io.loadmat</code></a> to load each <code>.mat</code> file.</p>",204          "post_number": 5,205          "post_type": 1,206          "posts_count": 4,207          "updated_at": "2022-08-02T16:29:50.225Z",208          "reply_count": 0,209          "reply_to_post_number": 4,210          "quote_count": 0,211          "incoming_link_count": 1,212          "reads": 7,213          "readers_count": 6,214          "score": 6.4,215          "yours": false,216          "topic_id": 158129,217          "topic_slug": "custom-dataloader-using-mat-file",218          "display_username": "",219          "primary_group_name": null,220          "flair_name": null,221          "flair_url": null,222          "flair_bg_color": null,223          "flair_color": null,224          "flair_group_id": null,225          "badges_granted": [],226          "version": 1,227 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"internal": false,668          "attachment": false,669          "reflection": false,670          "clicks": 13,671          "user_id": 3534,672          "domain": "docs.scipy.org",673          "root_domain": "scipy.org"674        }675      ]676    },677    "bookmarks": []678  },679  {680    "post_stream": {681      "posts": [682        {683          "id": 352733,684          "name": "",685          "username": "peppermint",686          "avatar_template": "/letter_avatar_proxy/v4/letter/p/dfb087/{size}.png",687          "created_at": "2022-06-21T16:57:01.271Z",688          "cooked": "<p><strong>TL;DR</strong>, does computing <code>torch.var(x)</code> on a 1D tensor of n values have a quadratic runtime with autograd? Or does autograd it have a linear runtime in n?</p>\n<p><strong>Longer version:</strong><br>\nIf I have n values in a 1D tensor, and I compute var within a nn.Module, will autograd compute an n by n Jacobian in quadratic runtime?</p>\n<p>For example, if we have values<br>\n<code>x = torch.tensor([1.,2.,4.,8.,16.,32.,64.], requires_grad=True)</code><br>\nthen <code>y = torch.var(x)</code> will set <code>grad_fn</code> in <code>y</code>.</p>\n<p>The variance can be conceptualized as computing all pairwise distances (with a quadratic number of operations) and shifting and scaling:<br>\n<code>torch.sum( (x.view(-1,1) - x.view(1,-1))**2 / (2*len(x)*(len(x)-1)) )</code></p>\n<p>Or the varaince can be conceptualized as caching the mean (with a linear number of operations), computing all distances to that mean (also linear) and then scaling the result:<br>\n<code>torch.sum( (x - torch.mean(x))**2 / (len(x)-1) )</code></p>\n<p>In the first way, it’s clear that all pairs of values in <code>x</code> affect <code>torch.var</code>, and so an n by n matrix will be computed by autograd.</p>\n<p>In the second (more standard way), the mean is cached, with autograd depicting a dependency of the mean on each value from <code>x</code>. Then, the mean collides with every value from <code>x</code> to compute the variance. So in this case, it appears the gradients will be quadratic as well. Is that the case?</p>\n<p>Also, how is there a way that I could’ve delved into <code>y.grad_fn</code> to determine this for myself without asking and without empirically measuring whether the runtimes seem to grow quadratically? Thank you!</p>",689          "post_number": 1,690          "post_type": 1,691          "posts_count": 2,692          "updated_at": "2022-06-21T16:57:01.271Z",693          "reply_count": 0,694          "reply_to_post_number": null,695          "quote_count": 0,696          "incoming_link_count": 13,697          "reads": 6,698          "readers_count": 5,699          "score": 66.2,700          "yours": false,701          "topic_id": 154717,702          "topic_slug": "does-autograd-on-var-give-a-quadratic-runtime",703          "display_username": "",704          "primary_group_name": null,705          "flair_name": null,706          "flair_url": null,707          "flair_bg_color": null,708          "flair_color": null,709          "flair_group_id": null,710          "badges_granted": [],711          "version": 1,712          "can_edit": false,713          "can_delete": false,714          "can_recover": false,715          "can_see_hidden_post": false,716          "can_wiki": false,717          "read": true,718          "user_title": null,719          "bookmarked": false,720          "actions_summary": [],721          "moderator": false,722          "admin": false,723          "staff": false,724          "user_id": 52851,725          "hidden": false,726          "trust_level": 1,727          "deleted_at": null,728          "user_deleted": false,729          "edit_reason": null,730          "can_view_edit_history": true,731          "wiki": false,732          "post_url": "/t/does-autograd-on-var-give-a-quadratic-runtime/154717/1",733          "can_accept_answer": false,734          "can_unaccept_answer": false,735          "accepted_answer": false,736          "topic_accepted_answer": null,737          "can_vote": false738        },739        {740          "id": 359587,741          "name": "",742          "username": "peppermint",743          "avatar_template": "/letter_avatar_proxy/v4/letter/p/dfb087/{size}.png",744          "created_at": "2022-08-02T16:25:59.808Z",745          "cooked": "<p>Just bumping this in case it got lost during summer holidays. Any thoughts are appreciated!</p>",746          "post_number": 2,747          "post_type": 1,748          "posts_count": 2,749          "updated_at": "2022-08-02T16:25:59.808Z",750          "reply_count": 0,751          "reply_to_post_number": null,752          "quote_count": 0,753          "incoming_link_count": 0,754          "reads": 5,755          "readers_count": 4,756          "score": 1.0,757          "yours": false,758          "topic_id": 154717,759          "topic_slug": "does-autograd-on-var-give-a-quadratic-runtime",760          "display_username": "",761          "primary_group_name": null,762          "flair_name": null,763          "flair_url": null,764          "flair_bg_color": null,765          "flair_color": null,766          "flair_group_id": null,767          "badges_granted": [],768          "version": 1,769          "can_edit": false,770          "can_delete": false,771          "can_recover": false,772          "can_see_hidden_post": false,773          "can_wiki": false,774          "read": true,775          "user_title": null,776          "bookmarked": false,777          "actions_summary": [],778          "moderator": false,779          "admin": false,780          "staff": false,781          "user_id": 52851,782          "hidden": false,783          "trust_level": 1,784          "deleted_at": null,785          "user_deleted": false,786          "edit_reason": null,787          "can_view_edit_history": true,788          "wiki": false,789          "post_url": "/t/does-autograd-on-var-give-a-quadratic-runtime/154717/2",790          "can_accept_answer": false,791          "can_unaccept_answer": false,792          "accepted_answer": false,793          "topic_accepted_answer": null794        }795      ],796      "stream": [797        352733,798        359587799      ]800    },801    "timeline_lookup": [802      [803        1,804        1222805      ],806      [807        2,808        1180809      ]810    ],811    "suggested_topics": [812      {813        "fancy_title": "Wrong dimension of per sample gradients",814        "id": 213902,815        "title": "Wrong dimension of per sample gradients",816        "slug": "wrong-dimension-of-per-sample-gradients",817        "posts_count": 2,818        "reply_count": 0,819        "highest_post_number": 2,820        "image_url": null,821        "created_at": "2024-12-06T08:56:22.607Z",822        "last_posted_at": "2024-12-09T15:45:35.401Z",823        "bumped": true,824        "bumped_at": "2024-12-09T15:45:35.401Z",825        "archetype": "regular",826        "unseen": false,827        "pinned": false,828        "unpinned": null,829        "visible": true,830        "closed": false,831        "archived": false,832        "bookmarked": null,833        "liked": null,834        "tags_descriptions": {},835        "like_count": 0,836        "views": 39,837        "category_id": 7,838        "featured_link": null,839        "has_accepted_answer": false,840        "posters": [841          {842            "extras": "latest single",843            "description": "Original Poster, Most Recent Poster",844            "user": {845              "id": 81353,846              "username": "jspieler",847              "name": "",848              "avatar_template": "/letter_avatar_proxy/v4/letter/j/aeb1de/{size}.png",849              "trust_level": 1850            }851          }852        ]853      },854      {855        "fancy_title": "Initializing tensor inside custom loss fn causes cuda memory err",856        "id": 217711,857        "title": "Initializing tensor inside custom loss fn causes cuda memory err",858        "slug": "initializing-tensor-inside-custom-loss-fn-causes-cuda-memory-err",859        "posts_count": 6,860        "reply_count": 4,861        "highest_post_number": 6,862        "image_url": null,863        "created_at": "2025-03-11T19:26:00.836Z",864        "last_posted_at": "2025-03-12T20:54:40.956Z",865        "bumped": true,866        "bumped_at": "2025-03-12T20:54:40.956Z",867        "archetype": "regular",868        "unseen": false,869        "pinned": false,870        "unpinned": null,871        "visible": true,872        "closed": false,873        "archived": false,874        "bookmarked": null,875        "liked": null,876        "tags_descriptions": {},877        "like_count": 0,878        "views": 150,879        "category_id": 7,880        "featured_link": null,881        "has_accepted_answer": false,882        "posters": [883          {884            "extras": null,885            "description": "Original Poster",886            "user": {887              "id": 29555,888              "username": "hectorist",889              "name": "Yusuf B. 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"/user_avatar/discuss.pytorch.org/sajastu/{size}/14519_2.png",1173          "created_at": "2022-08-02T15:48:10.468Z",1174          "cooked": "<p>I’m trying to run a Huggingface model on multi-GPU. The problem is that when I’m processing multiple inputs which are bound to each other from a single class (shared-weights), I’m getting <code>RuntimeError: Expected to mark a variable ready only once.</code>. While if I use the module only once, for processing one input, I won’t get this error.</p>\n<p>To make it clearer, here is the structure:</p>\n<pre><code class=\"lang-auto\">class Model():\n    \n    def __init__(self, ...)\n\t   self.encoder = ...\n\n\n    def forward(input_ids, ...):\n\n\t   encoder_outputs = self.encoder(input_ids, ...)\n\n\t   # filter encoder_outputs and construct another tensor called 'input_ids_selected'\n\n\t   encoder_outputs = self.encoder(input_ids_selected, ...)\n\n\n\t   return encoder_outputs\n</code></pre>\n<p>If I remove this line: <code>encoder_outputs = self.encoder(input_ids_selected, ...)</code>, I will not run into this error. Should say that to filter encoder_outputs from the first pass of encoder, I’m using other modules (linear layers) to find important <code>input_ids</code>, retaining those in <code>input_ids_selected</code>. You can see this as a two-step summarizer.</p>",1175          "post_number": 1,1176          "post_type": 1,1177          "posts_count": 1,1178          "updated_at": "2022-08-02T15:50:43.472Z",1179          "reply_count": 0,1180          "reply_to_post_number": null,1181          "quote_count": 0,1182          "incoming_link_count": 101,1183          "reads": 8,1184          "readers_count": 7,1185          "score": 506.6,1186          "yours": false,1187          "topic_id": 158147,1188          "topic_slug": "runtimeerror-expected-to-mark-a-variable-ready-only-once-on-multi-gpu-setting",1189          "display_username": "Sajad",1190          "primary_group_name": null,1191          "flair_name": null,1192          "flair_url": null,1193          "flair_bg_color": null,1194          "flair_color": null,1195          "flair_group_id": null,1196          "badges_granted": [],1197          "version": 1,1198          "can_edit": false,1199          "can_delete": false,1200          "can_recover": false,

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