Anurag1734/cuda-error-resolution-analysis
07
1[2 {3 "post_stream": {4 "posts": [5 {6 "id": 131904,7 "name": "John Cwok ",8 "username": "JohnCwok",9 "avatar_template": "/user_avatar/discuss.pytorch.org/johncwok/{size}/13001_2.png",10 "created_at": "2019-08-28T14:39:27.737Z",11 "cooked": "<p>I noticed that it is not possible to feed <code>packed_sequences</code> to things like activation functions or linear layers, forcing me to design models having a forward method like :</p>\n<pre><code class=\"lang-auto\"> def forward(self, input, lengths, hidden = None):\n input = nn.utils.rnn.pack_padded_sequence(input, lengths, batch_first = True, enforce_sorted = False)\n out, hidden = self.lstm(input,hidden)\n out = nn.utils.rnn.pad_packed_sequence(out, batch_first = True, padding_value= -100)[0]\n out = self.drop_layer(self.sigmoid(out))\n out = self.softmax(self.linear_layer(out))\n</code></pre>\n<p>Where I have to unpack the <code>packed_sequence</code> directly after the passing through <code>LSTM</code>, and later need to filter it before loss calculation. if I don’t, I received an error message :</p>\n<pre><code class=\"lang-auto\">TypeError: sigmoid(): argument 'input' (position 1) must be Tensor, not PackedSequence\n</code></pre>\n<p>This seem highly inefficient since a lot of the calculations done by the activations functions and linear layers will have to be thrown away afterwards.</p>\n<p>Why is that so ? What is the reason preventing us from passing <code>packed_sequences</code> to activation function or linear layers ?</p>",12 "post_number": 1,13 "post_type": 1,14 "posts_count": 1,15 "updated_at": "2019-08-28T14:39:27.737Z",16 "reply_count": 0,17 "reply_to_post_number": null,18 "quote_count": 0,19 "incoming_link_count": 16,20 "reads": 4,21 "readers_count": 3,22 "score": 80.8,23 "yours": false,24 "topic_id": 54580,25 "topic_slug": "optimize-batch-processing-of-variable-length-inputs",26 "display_username": "John Cwok ",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": 19525,48 "hidden": false,49 "trust_level": 2,50 "deleted_at": null,51 "user_deleted": false,52 "edit_reason": null,53 "can_view_edit_history": true,54 "wiki": false,55 "post_url": "/t/optimize-batch-processing-of-variable-length-inputs/54580/1",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 "stream": [64 13190465 ]66 },67 "timeline_lookup": [68 [69 1,70 225071 ]72 ],73 "suggested_topics": [74 {75 "fancy_title": "What’s the theoreticl basis of torch.testing tolerance table?",76 "id": 213255,77 "title": "What's the theoreticl basis of torch.testing tolerance table?",78 "slug": "whats-the-theoreticl-basis-of-torch-testing-tolerance-table",79 "posts_count": 1,80 "reply_count": 0,81 "highest_post_number": 1,82 "image_url": "https://discuss.pytorch.org/uploads/default/optimized/3X/7/0/704c9ddf26dc72ffe8f69312a123846fdab78ded_2_1024x736.png",83 "created_at": "2024-11-21T07:42:12.294Z",84 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It seems to be related to the ld linker",268 "id": 212866,269 "title": "Compile the PyTorch from source code by using Dockerfile, I got a fishy error. It seems to be related to the ld linker",270 "slug": "compile-the-pytorch-from-source-code-by-using-dockerfile-i-got-a-fishy-error-it-seems-to-be-related-to-the-ld-linker",271 "posts_count": 5,272 "reply_count": 3,273 "highest_post_number": 6,274 "image_url": null,275 "created_at": "2024-11-12T13:21:13.716Z",276 "last_posted_at": "2024-11-25T07:09:59.728Z",277 "bumped": true,278 "bumped_at": "2024-11-25T07:09:59.728Z",279 "archetype": "regular",280 "unseen": false,281 "pinned": false,282 "unpinned": null,283 "visible": true,284 "closed": false,285 "archived": false,286 "bookmarked": null,287 "liked": null,288 "tags_descriptions": {},289 "like_count": 1,290 "views": 90,291 "category_id": 1,292 "featured_link": null,293 "has_accepted_answer": true,294 "posters": [295 {296 "extras": "latest",297 "description": "Original Poster, Most Recent Poster, Accepted Answer",298 "user": {299 "id": 80843,300 "username": "shysuen001",301 "name": "",302 "avatar_template": "/user_avatar/discuss.pytorch.org/shysuen001/{size}/73944_2.png",303 "trust_level": 1304 }305 },306 {307 "extras": null,308 "description": "Frequent Poster",309 "user": {310 "id": 3534,311 "username": "ptrblck",312 "name": "",313 "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",314 "admin": true,315 "moderator": true,316 "trust_level": 2317 }318 },319 {320 "extras": null,321 "description": "Frequent Poster",322 "user": {323 "id": 81111,324 "username": "sgomber",325 "name": "Shaurya Gomber",326 "avatar_template": "/user_avatar/discuss.pytorch.org/sgomber/{size}/74173_2.png",327 "trust_level": 1328 }329 }330 ]331 }332 ],333 "tags_descriptions": {},334 "fancy_title": "Optimize batch processing of variable-length inputs",335 "id": 54580,336 "title": "Optimize batch processing of variable-length inputs",337 "posts_count": 1,338 "created_at": "2019-08-28T14:39:27.687Z",339 "views": 288,340 "reply_count": 0,341 "like_count": 0,342 "last_posted_at": "2019-08-28T14:39:27.737Z",343 "visible": true,344 "closed": false,345 "archived": false,346 "has_summary": false,347 "archetype": "regular",348 "slug": "optimize-batch-processing-of-variable-length-inputs",349 "category_id": 1,350 "word_count": 161,351 "deleted_at": null,352 "user_id": 19525,353 "featured_link": null,354 "pinned_globally": false,355 "pinned_at": null,356 "pinned_until": null,357 "image_url": null,358 "slow_mode_seconds": 0,359 "draft": null,360 "draft_key": "topic_54580",361 "draft_sequence": null,362 "unpinned": null,363 "pinned": false,364 "current_post_number": 1,365 "highest_post_number": 1,366 "deleted_by": null,367 "actions_summary": [368 {369 "id": 4,370 "count": 0,371 "hidden": false,372 "can_act": false373 },374 {375 "id": 8,376 "count": 0,377 "hidden": false,378 "can_act": false379 },380 {381 "id": 10,382 "count": 0,383 "hidden": false,384 "can_act": false385 },386 {387 "id": 7,388 "count": 0,389 "hidden": false,390 "can_act": false391 }392 ],393 "chunk_size": 20,394 "bookmarked": false,395 "topic_timer": null,396 "message_bus_last_id": 0,397 "participant_count": 1,398 "show_read_indicator": false,399 "thumbnails": null,400 "slow_mode_enabled_until": null,401 "can_vote": false,402 "vote_count": 0,403 "user_voted": false,404 "discourse_zendesk_plugin_zendesk_id": null,405 "discourse_zendesk_plugin_zendesk_url": "https://your-url.zendesk.com/agent/tickets/",406 "details": {407 "can_edit": false,408 "notification_level": 1,409 "participants": [410 {411 "id": 19525,412 "username": "JohnCwok",413 "name": "John Cwok ",414 "avatar_template": "/user_avatar/discuss.pytorch.org/johncwok/{size}/13001_2.png",415 "post_count": 1,416 "primary_group_name": null,417 "flair_name": null,418 "flair_url": null,419 "flair_color": null,420 "flair_bg_color": null,421 "flair_group_id": null,422 "trust_level": 2423 }424 ],425 "created_by": {426 "id": 19525,427 "username": "JohnCwok",428 "name": "John Cwok ",429 "avatar_template": "/user_avatar/discuss.pytorch.org/johncwok/{size}/13001_2.png"430 },431 "last_poster": {432 "id": 19525,433 "username": "JohnCwok",434 "name": "John Cwok ",435 "avatar_template": "/user_avatar/discuss.pytorch.org/johncwok/{size}/13001_2.png"436 }437 },438 "bookmarks": []439 },440 {441 "post_stream": {442 "posts": [443 {444 "id": 130426,445 "name": "",446 "username": "tholzmann",447 "avatar_template": "/letter_avatar_proxy/v4/letter/t/c57346/{size}.png",448 "created_at": "2019-08-21T09:27:59.844Z",449 "cooked": "<p>Hi,</p>\n<p>I am using PyTorch 1.2.0 self-compiled with CUDA compute capability 5.2 with C++ and everything works as expected.</p>\n<p>I read somewhere that everything down to compute capability 3.5 is supported. Hence, as we aim to support as many graphic cards as possible, i tried to compile PyTorch with compute capability 3.5. However, I get an error when using this version:</p>\n<blockquote>\n<p>.THCudaCheck FAIL file=D:/tools/pytorch-v1.2.0/aten/src\\THC/generic/THCTensorMath.cu line=16 error=209 : no kernel image is available for execution on the device<br>\nexception message: cuda runtime error (209) : no kernel image is available for execution on the device at D:/tools/pytorch-v1.2.0/aten/src\\THC/generic/THCTensorMath.cu:16<br>\nThe above operation failed in interpreter, with the following stack trace:<br>\nat code/model-input_rgbip-output_14classes_best_train_2019_08_03_cpu-eval-mode-export_latest_pytorch.py:292:12<br>\n_135 = getattr(_131, “1”)<br>\n_136 = _135.weight<br>\n_137 = _135.bias<br>\n_138 = getattr(self.decoder0, “0”)<br>\n_139 = _138.weight<br>\n_140 = _138.bias<br>\n_141 = getattr(self.logit, “0”)<br>\n_142 = _141.weight<br>\n_143 = _141.bias<br>\ninput0 = torch._convolution(input, <em>1, None, [2, 2], [3, 3], [1, 1], False, [0, 0], 1, True, False, True)<br>\n~~~~~~~~~~~~~~~~~~ <— HERE<br>\ninput1 = torch.batch_norm(input0, weight, bias, running_mean, running_var, False, 0.10000000000000001, 1.0000000000000001e-05, True)<br>\ninput2 = torch.relu</em>(input1)<br>\ninput3 = torch.max_pool2d(input2, [3, 3], [2, 2], [1, 1], [1, 1], False)<br>\ninput4 = torch._convolution(input3, <em>5, None, [1, 1], [1, 1], [1, 1], False, [0, 0], 1, True, False, True)<br>\ninput5 = torch.batch_norm(input4, weight0, bias0, running_mean0, running_var0, False, 0.10000000000000001, 1.0000000000000001e-05, True)<br>\ninput6 = torch.relu</em>(input5)<br>\ninput7 = torch._convolution(input6, <em>7, None, [1, 1], [1, 1], [1, 1], False, [0, 0], 1, True, False, True)<br>\nout = torch.batch_norm(input7, weight1, bias1, running_mean1, running_var1, False, 0.10000000000000001, 1.0000000000000001e-05, True)<br>\ninput8 = torch.add</em>(out, input3, alpha=1)Compiled from code /opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(340): forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(523): _slow_forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(537): <strong>call</strong><br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/container.py(92): forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(523): _slow_forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(537): <strong>call</strong><br>\n…/dl/models/unet.py(153): forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(523): _slow_forward<br>\n/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(537): <strong>call</strong><br>\n/opt/conda/lib/python3.6/site-packages/torch/jit/<strong>init</strong>.py(883): trace_module<br>\n/opt/conda/lib/python3.6/site-packages/torch/jit/<strong>init</strong>.py(751): trace<br>\n(5): <br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(3296): run_code<br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(3214): run_ast_nodes<br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(3049): run_cell_async<br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/async_helpers.py(67): _pseudo_sync_runner<br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2874): _run_cell<br>\n/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2848): run_cell<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py(536): run_cell<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py(294): do_execute<br>\n/opt/conda/lib/python3.6/site-packages/tornado/gen.py(209): wrapper<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(534): execute_request<br>\n/opt/conda/lib/python3.6/site-packages/tornado/gen.py(209): wrapper<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(267): dispatch_shell<br>\n/opt/conda/lib/python3.6/site-packages/tornado/gen.py(209): wrapper<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(357): process_one<br>\n/opt/conda/lib/python3.6/site-packages/tornado/gen.py(742): run<br>\n/opt/conda/lib/python3.6/site-packages/tornado/gen.py(781): inner<br>\n/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py(743): _run_callback<br>\n/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py(690): <br>\n/opt/conda/lib/python3.6/asyncio/events.py(145): _run<br>\n/opt/conda/lib/python3.6/asyncio/base_events.py(1451): _run_once<br>\n/opt/conda/lib/python3.6/asyncio/base_events.py(438): run_forever<br>\n/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(148): start<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py(505): start<br>\n/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py(658): launch_instance<br>\n/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py(16): <br>\n/opt/conda/lib/python3.6/runpy.py(85): _run_code<br>\n/opt/conda/lib/python3.6/runpy.py(193): _run_module_as_main</p>\n</blockquote>\n<p>So I assume compute capability 3.5 is also not fully supported anymore?<br>\nDown to which compute capability PyTorch 1.2.0 should work correctly?</p>\n<p>My system:<br>\nWindows 10<br>\nVisual Studio 2019 - CUDA 10.1<br>\nPython 3.7<br>\nSelf-Compiled PyTorch 1.2.0</p>\n<p>Thanks!</p>\n<p>Best,<br>\nThomas</p>",450 "post_number": 1,451 "post_type": 1,452 "posts_count": 5,453 "updated_at": "2019-08-21T09:27:59.844Z",454 "reply_count": 0,455 "reply_to_post_number": null,456 "quote_count": 0,457 "incoming_link_count": 1542,458 "reads": 52,459 "readers_count": 51,460 "score": 7720.4,461 "yours": false,462 "topic_id": 53916,463 "topic_slug": "pytorch-1-2-0-with-compute-capability-3-5",464 "display_username": "",465 "primary_group_name": null,466 "flair_name": null,467 "flair_url": null,468 "flair_bg_color": null,469 "flair_color": null,470 "flair_group_id": null,471 "badges_granted": [],472 "version": 1,473 "can_edit": false,474 "can_delete": false,475 "can_recover": false,476 "can_see_hidden_post": false,477 "can_wiki": false,478 "read": true,479 "user_title": null,480 "bookmarked": false,481 "actions_summary": [],482 "moderator": false,483 "admin": false,484 "staff": false,485 "user_id": 21788,486 "hidden": false,487 "trust_level": 1,488 "deleted_at": null,489 "user_deleted": false,490 "edit_reason": null,491 "can_view_edit_history": true,492 "wiki": false,493 "post_url": "/t/pytorch-1-2-0-with-compute-capability-3-5/53916/1",494 "can_accept_answer": false,495 "can_unaccept_answer": false,496 "accepted_answer": false,497 "topic_accepted_answer": null,498 "can_vote": false499 },500 {501 "id": 130517,502 "name": "",503 "username": "tholzmann",504 "avatar_template": "/letter_avatar_proxy/v4/letter/t/c57346/{size}.png",505 "created_at": "2019-08-21T14:40:06.147Z",506 "cooked": "<p>I tried to build with compute capability 5.0 now, and this build is working. So I assume PyTorch requires 5.0 as minimum compute capability. Is this correct?</p>",507 "post_number": 2,508 "post_type": 1,509 "posts_count": 5,510 "updated_at": "2019-08-21T14:40:06.147Z",511 "reply_count": 1,512 "reply_to_post_number": null,513 "quote_count": 0,514 "incoming_link_count": 0,515 "reads": 42,516 "readers_count": 41,517 "score": 13.4,518 "yours": false,519 "topic_id": 53916,520 "topic_slug": "pytorch-1-2-0-with-compute-capability-3-5",521 "display_username": "",522 "primary_group_name": null,523 "flair_name": null,524 "flair_url": null,525 "flair_bg_color": null,526 "flair_color": null,527 "flair_group_id": null,528 "badges_granted": [],529 "version": 1,530 "can_edit": false,531 "can_delete": false,532 "can_recover": false,533 "can_see_hidden_post": false,534 "can_wiki": false,535 "read": true,536 "user_title": null,537 "bookmarked": false,538 "actions_summary": [],539 "moderator": false,540 "admin": false,541 "staff": false,542 "user_id": 21788,543 "hidden": false,544 "trust_level": 1,545 "deleted_at": null,546 "user_deleted": false,547 "edit_reason": null,548 "can_view_edit_history": true,549 "wiki": false,550 "post_url": "/t/pytorch-1-2-0-with-compute-capability-3-5/53916/2",551 "can_accept_answer": false,552 "can_unaccept_answer": false,553 "accepted_answer": false,554 "topic_accepted_answer": null555 },556 {557 "id": 130568,558 "name": "Alban D",559 "username": "albanD",560 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png",561 "created_at": "2019-08-21T19:03:33.264Z",562 "cooked": "<p>Hi,</p>\n<p>The comments about pytorch working all the way down to cc3.5 are quite old. I’m afraid this is not true anymore.</p>",563 "post_number": 3,564 "post_type": 1,565 "posts_count": 5,566 "updated_at": "2019-08-21T19:03:33.264Z",567 "reply_count": 1,568 "reply_to_post_number": 2,569 "quote_count": 0,570 "incoming_link_count": 1,571 "reads": 45,572 "readers_count": 44,573 "score": 19.0,574 "yours": false,575 "topic_id": 53916,576 "topic_slug": "pytorch-1-2-0-with-compute-capability-3-5",577 "display_username": "Alban D",578 "primary_group_name": null,579 "flair_name": null,580 "flair_url": null,581 "flair_bg_color": null,582 "flair_color": null,583 "flair_group_id": null,584 "badges_granted": [],585 "version": 1,586 "can_edit": false,587 "can_delete": false,588 "can_recover": false,589 "can_see_hidden_post": false,590 "can_wiki": false,591 "read": true,592 "user_title": "",593 "reply_to_user": {594 "id": 21788,595 "username": "tholzmann",596 "name": "",597 "avatar_template": "/letter_avatar_proxy/v4/letter/t/c57346/{size}.png"598 },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 "deleted_at": null,608 "user_deleted": false,609 "edit_reason": null,610 "can_view_edit_history": true,611 "wiki": false,612 "post_url": "/t/pytorch-1-2-0-with-compute-capability-3-5/53916/3",613 "can_accept_answer": false,614 "can_unaccept_answer": false,615 "accepted_answer": false,616 "topic_accepted_answer": null617 },618 {619 "id": 131042,620 "name": "Pu Jiachen",621 "username": "peterjc123",622 "avatar_template": "/user_avatar/discuss.pytorch.org/peterjc123/{size}/2790_2.png",623 "created_at": "2019-08-24T06:33:39.575Z",624 "cooked": "<p><aside class=\"onebox githubblob\">\n <header class=\"source\">\n <a href=\"https://github.com/pytorch/builder/blob/master/conda/pytorch-1.1.0/bld.bat#L18\" target=\"_blank\" rel=\"nofollow noopener\">github.com</a>\n </header>\n <article class=\"onebox-body\">\n <h4><a href=\"https://github.com/pytorch/builder/blob/master/conda/pytorch-1.1.0/bld.bat#L18\" target=\"_blank\" rel=\"nofollow noopener\">pytorch/builder/blob/master/conda/pytorch-1.1.0/bld.bat#L18</a></h4>\n<pre class=\"onebox\"><code class=\"lang-bat\"><ol class=\"start lines\" start=\"8\" style=\"counter-reset: li-counter 7 ;\">\n<li> set build_with_cuda=</li>\n<li>) else (</li>\n<li> set build_with_cuda=1</li>\n<li> set desired_cuda=%CUDA_VERSION:~0,-1%.%CUDA_VERSION:~-1,1%</li>\n<li>)</li>\n<li>\n</li>\n<li>if \"%build_with_cuda%\" == \"\" goto cuda_flags_end</li>\n<li>\n</li>\n<li>set CUDA_PATH=C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v%desired_cuda%</li>\n<li>set CUDA_BIN_PATH=%CUDA_PATH%\\bin</li>\n<li class=\"selected\">set TORCH_CUDA_ARCH_LIST=3.5;5.0+PTX</li>\n<li>if \"%desired_cuda%\" == \"8.0\" set TORCH_CUDA_ARCH_LIST=%TORCH_CUDA_ARCH_LIST%;6.0;6.1</li>\n<li>if \"%desired_cuda%\" == \"9.0\" set TORCH_CUDA_ARCH_LIST=%TORCH_CUDA_ARCH_LIST%;6.0;7.0</li>\n<li>if \"%desired_cuda%\" == \"9.2\" set TORCH_CUDA_ARCH_LIST=%TORCH_CUDA_ARCH_LIST%;6.0;6.1;7.0</li>\n<li>if \"%desired_cuda%\" == \"10.0\" set TORCH_CUDA_ARCH_LIST=%TORCH_CUDA_ARCH_LIST%;6.0;6.1;7.0;7.5</li>\n<li>set TORCH_NVCC_FLAGS=-Xfatbin -compress-all</li>\n<li>\n</li>\n<li>:cuda_flags_end</li>\n<li>\n</li>\n<li>set DISTUTILS_USE_SDK=1</li>\n<li>\n</li>\n</ol></code></pre>\n\n\n </article>\n <div class=\"onebox-metadata\">\n \n \n </div>\n <div style=\"clear: both\"></div>\n</aside>\n<br>\n<aside class=\"onebox githubblob\">\n <header class=\"source\">\n <a href=\"https://github.com/pytorch/builder/blob/master/windows/cuda100.bat#L36\" target=\"_blank\" rel=\"nofollow noopener\">github.com</a>\n </header>\n <article class=\"onebox-body\">\n <h4><a href=\"https://github.com/pytorch/builder/blob/master/windows/cuda100.bat#L36\" target=\"_blank\" rel=\"nofollow noopener\">pytorch/builder/blob/master/windows/cuda100.bat#L36</a></h4>\n<pre class=\"onebox\"><code class=\"lang-bat\"><ol class=\"start lines\" start=\"26\" style=\"counter-reset: li-counter 25 ;\">\n<li> echo NVTX ^(Visual Studio Extension ^for CUDA^) ^not installed, failing</li>\n<li> exit /b 1</li>\n<li> goto optcheck</li>\n<li>)</li>\n<li>\n</li>\n<li>IF \"%CUDA_PATH_V10_0%\"==\"\" (</li>\n<li> echo CUDA 10.0 not found, failing</li>\n<li> exit /b 1</li>\n<li>) ELSE (</li>\n<li> IF \"%BUILD_VISION%\" == \"\" (</li>\n<li class=\"selected\"> set TORCH_CUDA_ARCH_LIST=3.5;5.0+PTX;6.0;6.1;7.0;7.5</li>\n<li> set TORCH_NVCC_FLAGS=-Xfatbin -compress-all</li>\n<li> ) ELSE (</li>\n<li> set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_50,code=compute_50</li>\n<li> )</li>\n<li>\n</li>\n<li> set \"CUDA_PATH=%CUDA_PATH_V10_0%\"</li>\n<li> set \"PATH=%CUDA_PATH_V10_0%\\bin;%PATH%\"</li>\n<li>)</li>\n<li>\n</li>\n<li>:optcheck</li>\n</ol></code></pre>\n\n\n </article>\n <div class=\"onebox-metadata\">\n \n \n </div>\n <div style=\"clear: both\"></div>\n</aside>\n<br>\n<aside class=\"onebox githubblob\">\n <header class=\"source\">\n <a href=\"https://github.com/pytorch/builder/blob/master/windows/cuda90.bat#L36\" target=\"_blank\" rel=\"nofollow noopener\">github.com</a>\n </header>\n <article class=\"onebox-body\">\n <h4><a href=\"https://github.com/pytorch/builder/blob/master/windows/cuda90.bat#L36\" target=\"_blank\" rel=\"nofollow noopener\">pytorch/builder/blob/master/windows/cuda90.bat#L36</a></h4>\n<pre class=\"onebox\"><code class=\"lang-bat\"><ol class=\"start lines\" start=\"26\" style=\"counter-reset: li-counter 25 ;\">\n<li> echo NVTX ^(Visual Studio Extension ^for CUDA^) ^not installed, failing</li>\n<li> exit /b 1</li>\n<li> goto optcheck</li>\n<li>)</li>\n<li>\n</li>\n<li>IF \"%CUDA_PATH_V9_0%\"==\"\" (</li>\n<li> echo CUDA 9 not found, failing</li>\n<li> exit /b 1</li>\n<li>) ELSE (</li>\n<li> IF \"%BUILD_VISION%\" == \"\" (</li>\n<li class=\"selected\"> set TORCH_CUDA_ARCH_LIST=3.5;5.0+PTX;6.0;7.0</li>\n<li> set TORCH_NVCC_FLAGS=-Xfatbin -compress-all</li>\n<li> ) ELSE (</li>\n<li> set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_50,code=compute_50</li>\n<li> )</li>\n<li>\n</li>\n<li> set \"CUDA_PATH=%CUDA_PATH_V9_0%\"</li>\n<li> set \"PATH=%CUDA_PATH_V9_0%\\bin;%PATH%\"</li>\n<li>)</li>\n<li>\n</li>\n<li>:optcheck</li>\n</ol></code></pre>\n\n\n </article>\n <div class=\"onebox-metadata\">\n \n \n </div>\n <div style=\"clear: both\"></div>\n</aside>\n<br>\nActually 3.5 is in the CUDA_ARCH_LIST, I wonder why that is not supported.</p>",625 "post_number": 4,626 "post_type": 1,627 "posts_count": 5,628 "updated_at": "2019-08-24T06:33:39.575Z",629 "reply_count": 1,630 "reply_to_post_number": 3,631 "quote_count": 0,632 "incoming_link_count": 64,633 "reads": 45,634 "readers_count": 44,635 "score": 349.0,636 "yours": false,637 "topic_id": 53916,638 "topic_slug": "pytorch-1-2-0-with-compute-capability-3-5",639 "display_username": "Pu Jiachen",640 "primary_group_name": null,641 "flair_name": null,642 "flair_url": null,643 "flair_bg_color": null,644 "flair_color": null,645 "flair_group_id": null,646 "badges_granted": [],647 "version": 1,648 "can_edit": false,649 "can_delete": false,650 "can_recover": false,651 "can_see_hidden_post": false,652 "can_wiki": false,653 "link_counts": [654 {655 "url": "https://github.com/pytorch/builder/blob/master/conda/pytorch-1.1.0/bld.bat#L18",656 "internal": false,657 "reflection": false,658 "title": "builder/bld.bat at master · pytorch/builder · GitHub",659 "clicks": 7660 },661 {662 "url": "https://github.com/pytorch/builder/blob/master/windows/cuda100.bat#L36",663 "internal": false,664 "reflection": false,665 "title": "builder/cuda100.bat at master · pytorch/builder · GitHub",666 "clicks": 6667 },668 {669 "url": "https://github.com/pytorch/builder/blob/master/windows/cuda90.bat#L36",670 "internal": false,671 "reflection": false,672 "title": "builder/cuda90.bat at master · pytorch/builder · GitHub",673 "clicks": 0674 }675 ],676 "read": true,677 "user_title": null,678 "reply_to_user": {679 "id": 211,680 "username": "albanD",681 "name": "Alban D",682 "avatar_template": "/user_avatar/discuss.pytorch.org/alband/{size}/215_2.png"683 },684 "bookmarked": false,685 "actions_summary": [686 {687 "id": 2,688 "count": 1689 }690 ],691 "moderator": false,692 "admin": false,693 "staff": false,694 "user_id": 4802,695 "hidden": false,696 "trust_level": 2,697 "deleted_at": null,698 "user_deleted": false,699 "edit_reason": null,700 "can_view_edit_history": true,701 "wiki": false,702 "post_url": "/t/pytorch-1-2-0-with-compute-capability-3-5/53916/4",703 "can_accept_answer": false,704 "can_unaccept_answer": false,705 "accepted_answer": false,706 "topic_accepted_answer": null707 },708 {709 "id": 131887,710 "name": "",711 "username": "tholzmann",712 "avatar_template": "/letter_avatar_proxy/v4/letter/t/c57346/{size}.png",713 "created_at": "2019-08-28T13:52:09.565Z",714 "cooked": "<p>Interestingly, when I use the prebuild windows version built with CUDA/CuDNN, it works on a graphics card with cc 3.7 (Tesla K80). However, when I build pytorch myself with CUDA but without CuDNN, it does not work on this graphics card.</p>\n<p>Is it possible that some instructions are only implemented for a higher cc in CUDA, but if CuDNN is used these instructions are implemented with CuDNN and hence it works?</p>",715 "post_number": 5,716 "post_type": 1,717 "posts_count": 5,718 "updated_at": "2019-08-28T13:52:09.565Z",719 "reply_count": 0,720 "reply_to_post_number": 4,721 "quote_count": 0,722 "incoming_link_count": 11,723 "reads": 30,724 "readers_count": 29,725 "score": 61.0,726 "yours": false,727 "topic_id": 53916,728 "topic_slug": "pytorch-1-2-0-with-compute-capability-3-5",729 "display_username": "",730 "primary_group_name": null,731 "flair_name": null,732 "flair_url": null,733 "flair_bg_color": null,734 "flair_color": null,735 "flair_group_id": null,736 "badges_granted": [],737 "version": 1,738 "can_edit": false,739 "can_delete": false,740 "can_recover": false,741 "can_see_hidden_post": false,742 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