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Anurag1734/cuda-error-resolution-analysis

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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 313825,7          "name": "nikiguo",8          "username": "nikiguo93",9          "avatar_template": "/user_avatar/discuss.pytorch.org/nikiguo93/{size}/30791_2.png",10          "created_at": "2021-10-27T11:54:29.534Z",11          "cooked": "<p>Hi all. I want to create a linear layer and then initialize it with specific weights(I have a .sav file). Can anybody tell me how to realize it with pytorch?<br>\nafter doing this I should discard some layers of pretrained alexnet and add this linear layer to the alexnet. Can anybody tell me how to realize that with pytorch?</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 4,15          "updated_at": "2021-10-27T11:54:29.534Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 1121,20          "reads": 16,21          "readers_count": 15,22          "score": 5603.2,23          "yours": false,24          "topic_id": 135239,25          "topic_slug": "how-to-create-a-linear-layer-and-initialize-it-with-specific-weight",26          "display_username": "nikiguo",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": 44418,48          "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/how-to-create-a-linear-layer-and-initialize-it-with-specific-weight/135239/1",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": 313886,64          "name": "",65          "username": "ptrblck",66          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",67          "created_at": "2021-10-27T19:22:07.981Z",68          "cooked": "<p>You can load parameters via:</p>\n<pre><code class=\"lang-python\">with torch.no_grad():\n    model.layer.weight.copy_(custom_weight_tensor)\n</code></pre>\n<p>I don’t know exactly what “discard” layers means, but in case you want to remove them you could write a custom model and reuse other layers or replace them with <code>nn.Identity</code> assuming that the shapes of the activations would still match.</p>",69          "post_number": 2,70          "post_type": 1,71          "posts_count": 4,72          "updated_at": "2021-10-27T19:22:07.981Z",73          "reply_count": 1,74          "reply_to_post_number": null,75          "quote_count": 0,76          "incoming_link_count": 8,77          "reads": 16,78          "readers_count": 15,79          "score": 48.2,80          "yours": false,81          "topic_id": 135239,82          "topic_slug": "how-to-create-a-linear-layer-and-initialize-it-with-specific-weight",83          "display_username": "",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          "read": true,98          "user_title": "",99          "bookmarked": false,100          "actions_summary": [],101          "moderator": true,102          "admin": true,103          "staff": true,104          "user_id": 3534,105          "hidden": false,106          "trust_level": 2,107          "deleted_at": null,108          "user_deleted": false,109          "edit_reason": null,110          "can_view_edit_history": true,111          "wiki": false,112          "post_url": "/t/how-to-create-a-linear-layer-and-initialize-it-with-specific-weight/135239/2",113          "can_accept_answer": false,114          "can_unaccept_answer": false,115          "accepted_answer": false,116          "topic_accepted_answer": null117        },118        {119          "id": 315071,120          "name": "nikiguo",121          "username": "nikiguo93",122          "avatar_template": "/user_avatar/discuss.pytorch.org/nikiguo93/{size}/30791_2.png",123          "created_at": "2021-11-03T11:21:34.525Z",124          "cooked": "<p>Hi, thank you for your information. I trained a linear regression model and now I want to use these weights and bias from linear regression model to initialize the linear layer. I hope that the linear layer can behave like the linear regression model. how to realize that?</p>",125          "post_number": 3,126          "post_type": 1,127          "posts_count": 4,128          "updated_at": "2021-11-03T11:21:34.525Z",129          "reply_count": 1,130          "reply_to_post_number": 2,131          "quote_count": 0,132          "incoming_link_count": 2,133          "reads": 14,134          "readers_count": 13,135          "score": 17.8,136          "yours": false,137          "topic_id": 135239,138          "topic_slug": "how-to-create-a-linear-layer-and-initialize-it-with-specific-weight",139          "display_username": "nikiguo",140          "primary_group_name": null,141          "flair_name": null,142          "flair_url": null,143          "flair_bg_color": null,144          "flair_color": null,145          "flair_group_id": null,146          "badges_granted": [],147          "version": 1,148          "can_edit": false,149          "can_delete": false,150  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     "accepted_answer": false,178          "topic_accepted_answer": null179        },180        {181          "id": 315193,182          "name": "",183          "username": "ptrblck",184          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",185          "created_at": "2021-11-03T18:30:59.494Z",186          "cooked": "<p>I don’t know how the architecture of the linear regression model looks like, but in case it’s using non-linear activation functions you wouldn’t be able to squeeze this model into a single linear layer.<br>\nOtherwise I would assume that training a single linear layer would also work for your use case.</p>",187          "post_number": 4,188          "post_type": 1,189          "posts_count": 4,190          "updated_at": "2021-11-03T18:30:59.494Z",191          "reply_count": 0,192          "reply_to_post_number": 3,193          "quote_count": 0,194          "incoming_link_count": 3,195          "reads": 12,196          "readers_count": 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314802,659          "name": "Suho Cho",660          "username": "thecho7",661          "avatar_template": "/letter_avatar_proxy/v4/letter/t/eada6e/{size}.png",662          "created_at": "2021-11-02T07:55:56.338Z",663          "cooked": "<p>I found out the imbalance of GPU usages on my implementation.</p>\n<pre><code>def train(device, args):\n    torch.distributed.init_process_group(backend='nccl', rank=device, world_size=torch.cuda_device_count())\n    model_A = A()\n    model_B = B()\n    \n    # Not gonna update A\n    model_A.to(device)\n    ckpt = torch.load(path)\n    model_A.load_state_dict(ckpt['model_state_dict '])\n    model_A = torch.nn.parallel.DIstributedDataParallel(model_A, device_ids=[device])\n    model_A.eval()\n\n    # Gonna update B\n    model_B.to(device)\n    model_B = torch.nn.parallel.DistributedDataParallel(model_B, device_ids=[device])\n    model_B.train()        \n\nif __name__ == '__main__':\n    args = argparse()\n    torch.multiprocessing.spawn(train, nprocs=torch.cuda.device_count(), args=(args, ))\n</code></pre>\n<p>I intend to load both models A and B on GPUs however,<br>\nGPU usage tells me only model_A is allocated on GPU:0 and not allocated on the other GPUs.<br>\nlike below,</p>\n<p>GPU 0: 7000MiB / 11019MiB (model A, B)<br>\nGPU 1: 4000MiB / 11019MiB (model B)<br>\nGPU 2: 4000MiB / 11019MiB (model B)<br>\nGPU 3: 4000MiB / 11019MiB (model B)</p>\n<p>Please ask me free if you have any unclears.</p>",664          "post_number": 1,665          "post_type": 1,666          "posts_count": 4,667          "updated_at": "2021-11-03T00:17:13.492Z",668          "reply_count": 0,669          "reply_to_post_number": null,670          "quote_count": 0,671          "incoming_link_count": 364,672          "reads": 19,673          "readers_count": 18,674          "score": 1818.8,675          "yours": false,676          "topic_id": 135706,677          "topic_slug": "load-multiple-models-with-distributeddataparallel",678          "display_username": "Suho Cho",679          "primary_group_name": null,680          "flair_name": null,681          "flair_url": null,682          "flair_bg_color": null,683          "flair_color": null,684          "flair_group_id": null,685          "badges_granted": [],686          "version": 3,687          "can_edit": false,688          "can_delete": false,689          "can_recover": false,690          "can_see_hidden_post": false,691          "can_wiki": false,692          "read": true,693          "user_title": "",694          "bookmarked": false,695          "actions_summary": [],696          "moderator": false,697          "admin": false,698          "staff": false,699          "user_id": 7263,700          "hidden": false,701          "trust_level": 2,702          "deleted_at": null,703          "user_deleted": false,704          "edit_reason": null,705          "can_view_edit_history": true,706          "wiki": false,707          "post_url": "/t/load-multiple-models-with-distributeddataparallel/135706/1",708          "can_accept_answer": false,709          "can_unaccept_answer": false,710          "accepted_answer": false,711          "topic_accepted_answer": true,712          "can_vote": false713        },714        {715          "id": 314851,716          "name": "Shen Li",717          "username": "mrshenli",718          "avatar_template": "/user_avatar/discuss.pytorch.org/mrshenli/{size}/12220_2.png",719          "created_at": "2021-11-02T14:46:18.531Z",720          "cooked": "<p>It could be all processes unintentionally created CUDA context on the default GPU (<code>cuda:0</code>). To avoid this situation, can you try setting <code>CUDA_VISIBLE_DEVICES</code> env var to a different device for each process, so that each process would only see one GPU?</p>",721          "post_number": 2,722          "post_type": 1,723          "posts_count": 4,724          "updated_at": "2021-11-02T14:46:18.531Z",725          "reply_count": 1,726          "reply_to_post_number": null,727          "quote_count": 0,728          "incoming_link_count": 2,729          "reads": 16,730          "readers_count": 15,731          "score": 18.2,732          "yours": false,733          "topic_id": 135706,734          "topic_slug": "load-multiple-models-with-distributeddataparallel",735          "display_username": "Shen Li",736          "primary_group_name": null,737          "flair_name": null,738          "flair_url": null,739          "flair_bg_color": null,740          "flair_color": null,741          "flair_group_id": null,742          "badges_granted": [],743          "version": 1,744          "can_edit": false,745          "can_delete": false,746          "can_recover": false,747          "can_see_hidden_post": false,748          "can_wiki": false,749          "read": true,750          "user_title": null,751          "bookmarked": false,752          "actions_summary": [],753          "moderator": false,754          "admin": false,755          "staff": false,756          "user_id": 17068,757          "hidden": false,758          "trust_level": 2,759          "deleted_at": null,760          "user_deleted": false,761          "edit_reason": null,762          "can_view_edit_history": true,763          "wiki": false,764          "post_url": "/t/load-multiple-models-with-distributeddataparallel/135706/2",765          "can_accept_answer": false,766          "can_unaccept_answer": false,767          "accepted_answer": false,768          "topic_accepted_answer": true769        },770        {771          "id": 314934,772          "name": "Suho Cho",773          "username": "thecho7",774          "avatar_template": "/letter_avatar_proxy/v4/letter/t/eada6e/{size}.png",775          "created_at": "2021-11-03T00:19:19.675Z",776          "cooked": "<p>I solved this issue by <strong>map_location='cpu’</strong><br>\nLoading pretrained model</p>\n<pre><code>ckpt = torch.load(path)\n</code></pre>\n<p>automatically allocates the parameters to GPU:0.<br>\nI cannot understand why until now, but it is solved by using map_location while I load the model.</p>\n<pre><code>ckpt = torch.load(path, map_location='cpu')\nmodel_A.load_state_dict(ckpt['model_state_dict '])\nmodel_A.to(device)</code></pre>",777          "post_number": 3,778          "post_type": 1,779          "posts_count": 4,780          "updated_at": "2021-11-03T01:26:47.307Z",781          "reply_count": 1,782          "reply_to_post_number": 2,783          "quote_count": 0,784          "incoming_link_count": 5,785          "reads": 17,786          "readers_count": 16,787          "score": 33.4,788          "yours": false,789          "topic_id": 135706,790          "topic_slug": "load-multiple-models-with-distributeddataparallel",791          "display_username": "Suho Cho",792          "primary_group_name": null,793          "flair_name": null,794          "flair_url": null,795          "flair_bg_color": null,796          "flair_color": null,797          "flair_group_id": null,798          "badges_granted": [],799          "version": 2,800          "can_edit": false,801          "can_delete": false,802          "can_recover": false,803          "can_see_hidden_post": false,804          "can_wiki": false,805          "read": true,806          "user_title": "",807          "reply_to_user": {808            "id": 17068,809            "username": "mrshenli",810            "name": "Shen Li",811            "avatar_template": "/user_avatar/discuss.pytorch.org/mrshenli/{size}/12220_2.png"812          },813          "bookmarked": false,814          "actions_summary": [],815          "moderator": false,816          "admin": false,817          "staff": false,818          "user_id": 7263,819          "hidden": false,820          "trust_level": 2,821          "deleted_at": null,822          "user_deleted": false,823          "edit_reason": null,824          "can_view_edit_history": true,825          "wiki": false,826          "post_url": "/t/load-multiple-models-with-distributeddataparallel/135706/3",827          "can_accept_answer": false,828          "can_unaccept_answer": false,829          "accepted_answer": true,830          "topic_accepted_answer": true831        },832        {833          "id": 315186,834          "name": "Shen Li",835          "username": "mrshenli",836          "avatar_template": "/user_avatar/discuss.pytorch.org/mrshenli/{size}/12220_2.png",837          "created_at": "2021-11-03T18:29:03.979Z",838          "cooked": "<blockquote>\n<p>I cannot understand why until now, but it is solved by using map_location while I load the model.</p>\n</blockquote>\n<p>I think this is because, all processes are trying to load the model to <code>cuda:0</code> by default if you don’t set <code>map_location</code> or <code>CUDA_VISIBLE_DEVICES</code>. BTW, does directly setting <code>map_location</code> to <code>device</code> work for you?</p>",839          "post_number": 4,840          "post_type": 1,841          "posts_count": 4,842          "updated_at": "2021-11-03T18:29:03.979Z",843          "reply_count": 0,844          "reply_to_post_number": 3,845          "quote_count": 0,846          "incoming_link_count": 2,847          "reads": 15,848          "readers_count": 14,849          "score": 13.0,850          "yours": false,851          "topic_id": 135706,852          "topic_slug": "load-multiple-models-with-distributeddataparallel",853          "display_username": "Shen Li",854          "primary_group_name": null,855          "flair_name": null,856          "flair_url": null,857          "flair_bg_color": null,858          "flair_color": null,859          "flair_group_id": null,860          "badges_granted": [],861          "version": 1,862          "can_edit": false,863          "can_delete": false,864          "can_recover": 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