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Anurag1734/cuda-error-resolution-analysis

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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 357026,7          "name": null,8          "username": "hitbuyi",9          "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png",10          "created_at": "2022-07-18T13:27:52.528Z",11          "cooked": "<p>I need some help on parameters of  torch.onnx.export(…)</p>\n<p>1, dynamic axes.what are backgrounds or application requirements for us to set dynamic axes?</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 5,15          "updated_at": "2022-07-18T13:37:32.999Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 369,20          "reads": 9,21          "readers_count": 8,22          "score": 1821.8,23          "yours": false,24          "topic_id": 156882,25          "topic_slug": "on-torch-onnx-export",26          "display_username": null,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": 2,35          "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": 50569,48          "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/on-torch-onnx-export/156882/1",56          "can_accept_answer": false,57          "can_unaccept_answer": false,58          "accepted_answer": false,59          "topic_accepted_answer": true,60          "can_vote": false61        },62        {63          "id": 357074,64          "name": "",65          "username": "ptrblck",66          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",67          "created_at": "2022-07-18T18:37:54.179Z",68          "cooked": "<p><code>dynamic_axes</code> can be used to specify dimensions with a dynamic shape (i.e. the shape is known at runtime and can change). Usually dynamic shapes are used in a temporal dimension or spatial dimensions.</p>",69          "post_number": 2,70          "post_type": 1,71          "posts_count": 5,72          "updated_at": "2022-07-18T18:37:54.179Z",73          "reply_count": 1,74          "reply_to_post_number": null,75          "quote_count": 0,76          "incoming_link_count": 0,77          "reads": 8,78          "readers_count": 7,79          "score": 6.6,80          "yours": false,81          "topic_id": 156882,82          "topic_slug": "on-torch-onnx-export",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/on-torch-onnx-export/156882/2",113          "can_accept_answer": false,114          "can_unaccept_answer": false,115          "accepted_answer": false,116          "topic_accepted_answer": true117        },118        {119          "id": 357114,120          "name": null,121          "username": "hitbuyi",122          "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png",123          "created_at": "2022-07-19T03:12:28.166Z",124          "cooked": "<p>I’m still not very clear, take temporal as example, if we take time as a dimension of input ,we can write the input tensor as</p>\n<p>input_image = [W H T]</p>\n<p>where  W is width, H is height, T is temporal</p>\n<p>dimension of input_image is 3(fixed), the value of T is changed  at every frame, in this example ,we should set T as dynamic axis?</p>\n<p>What I understand about dynamic shape is changing of dimensions, not value of a specified dimension, e.g.,</p>\n<p>at frame 1:  input_image = [W H T]<br>\nat frame 2:  input_image =[W H]</p>\n<p>this is called dynamic shape of input, right?</p>",125          "post_number": 3,126          "post_type": 1,127          "posts_count": 5,128          "updated_at": "2022-07-19T04:22:06.095Z",129          "reply_count": 1,130          "reply_to_post_number": 2,131          "quote_count": 0,132          "incoming_link_count": 2,133          "reads": 8,134          "readers_count": 7,135          "score": 16.6,136          "yours": false,137          "topic_id": 156882,138          "topic_slug": "on-torch-onnx-export",139          "display_username": null,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": 2,148          "can_edit": false,149          "can_delete": false,150          "can_recover": false,151          "can_see_hidden_post": false,152          "can_wiki": false,153          "read": true,154          "user_title": null,155          "reply_to_user": {156            "id": 3534,157            "username": "ptrblck",158            "name": "",159            "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png"160          },161          "bookmarked": false,162          "actions_summary": [],163          "moderator": false,164          "admin": false,165          "staff": false,166          "user_id": 50569,167     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src=\"https://discuss.pytorch.org/letter_avatar_proxy/v4/letter/h/ee59a6/48.png\" class=\"avatar\"> hitbuyi:</div>\n<blockquote>\n<p>What I understand about dynamic shape is changing of dimensions, not value of a specified dimension,</p>\n</blockquote>\n</aside>\n<p>No, usually you refer to a change in the actual shape. I.e. in one iteration the input shape could be <code>[1, 1, 1]</code> in the next it could be <code>[2, 3, 4]</code>.<br>\nDropping or adding an entire dimension would usually just fail at a layer input as a specific number of dimensions is expected.</p>",187          "post_number": 4,188          "post_type": 1,189          "posts_count": 5,190          "updated_at": "2022-07-19T04:18:20.597Z",191          "reply_count": 1,192          "reply_to_post_number": 3,193          "quote_count": 1,194          "incoming_link_count": 4,195          "reads": 8,196          "readers_count": 7,197          "score": 21.6,198          "yours": false,199          "topic_id": 156882,200          "topic_slug": "on-torch-onnx-export",201          "display_username": "",202          "primary_group_name": null,203          "flair_name": null,204          "flair_url": null,205          "flair_bg_color": null,206          "flair_color": null,207          "flair_group_id": null,208          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"username": "hitbuyi",240          "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png",241          "created_at": "2022-07-19T04:22:31.469Z",242          "cooked": "<p>Now I get the point, thanks a lot</p>",243          "post_number": 5,244          "post_type": 1,245          "posts_count": 5,246          "updated_at": "2022-07-19T04:22:31.469Z",247          "reply_count": 0,248          "reply_to_post_number": 4,249          "quote_count": 0,250          "incoming_link_count": 2,251          "reads": 7,252          "readers_count": 6,253          "score": 11.4,254          "yours": false,255          "topic_id": 156882,256          "topic_slug": "on-torch-onnx-export",257          "display_username": null,258          "primary_group_name": null,259          "flair_name": null,260          "flair_url": null,261          "flair_bg_color": null,262          "flair_color": null,263          "flair_group_id": null,264          "badges_granted": [],265          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I.e. in one iteration the input shape could be [1, 1, 1] in the next it could be [2, 3, 4]. \nDropping or adding an entire dimension would usually just fail at a layer input as a specific number of dimensions is expected."631    },632    "can_vote": false,633    "vote_count": 0,634    "user_voted": false,635    "discourse_zendesk_plugin_zendesk_id": null,636    "discourse_zendesk_plugin_zendesk_url": "https://your-url.zendesk.com/agent/tickets/",637    "details": {638      "can_edit": false,639      "notification_level": 1,640      "participants": [641        {642          "id": 50569,643          "username": "hitbuyi",644          "name": null,645          "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png",646          "post_count": 3,647          "primary_group_name": null,648          "flair_name": null,649          "flair_url": null,650          "flair_color": null,651          "flair_bg_color": null,652          "flair_group_id": null,653          "trust_level": 1654        },655        {656          "id": 3534,657          "username": "ptrblck",658          "name": "",659          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",660          "post_count": 2,661          "primary_group_name": null,662          "flair_name": null,663          "flair_url": null,664          "flair_color": null,665          "flair_bg_color": null,666          "flair_group_id": null,667          "admin": true,668          "moderator": true,669          "trust_level": 2670        }671      ],672      "created_by": {673        "id": 50569,674        "username": "hitbuyi",675        "name": null,676        "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png"677      },678      "last_poster": {679        "id": 50569,680        "username": "hitbuyi",681        "name": null,682        "avatar_template": "/letter_avatar_proxy/v4/letter/h/ee59a6/{size}.png"683      }684    },685    "bookmarks": []686  },687  {688    "post_stream": {689      "posts": [690        {691          "id": 357264,692          "name": "Apprehensive Oil 284",693          "username": "Apprehensive-oil-284",694          "avatar_template": "/user_avatar/discuss.pytorch.org/apprehensive-oil-284/{size}/51596_2.png",695          "created_at": "2022-07-19T20:07:59.923Z",696          "cooked": "<p>Consider the following code:</p>\n<pre><code class=\"lang-auto\">import time\n\nimport torch\n\n\nif __name__ == '__main__':\n    seed = 0\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    torch.cuda.manual_seed_all(seed)\n\n    x = torch.rand(32, 256, 220, 220).cuda()\n\n    t = (x.min() - x.max()).to(torch.device(\"cpu\"), non_blocking=True)\n    print(t)\n    time.sleep(2.)\n    print(t)\n</code></pre>\n<p>and it will print:</p>\n<pre><code class=\"lang-auto\">tensor(0.)\ntensor(-1.0000)\n</code></pre>\n<p>as in the first print, the data is not transmitted to host yet. My question is, is there some way to synchronize with it? In particular, is there something I can do with CUDA stream and Event?</p>",697          "post_number": 1,698          "post_type": 1,699          "posts_count": 5,700          "updated_at": "2022-07-19T20:07:59.923Z",701          "reply_count": 0,702          "reply_to_post_number": null,703          "quote_count": 0,704          "incoming_link_count": 1648,705          "reads": 68,706          "readers_count": 67,707          "score": 8218.6,708          "yours": false,709          "topic_id": 157010,710          "topic_slug": "how-to-wait-on-non-blocking-copying-from-gpu-to-cpu",711          "display_username": "Apprehensive Oil 284",712          "primary_group_name": null,713          "flair_name": null,714          "flair_url": null,715          "flair_bg_color": null,716          "flair_color": null,717          "flair_group_id": null,718          "badges_granted": [],719          "version": 1,720          "can_edit": false,721          "can_delete": false,722          "can_recover": false,723          "can_see_hidden_post": false,724          "can_wiki": false,725          "read": true,726          "user_title": null,727          "bookmarked": false,728          "actions_summary": [729            {730              "id": 2,731              "count": 1732            }733          ],734          "moderator": false,735          "admin": false,736          "staff": false,737          "user_id": 57802,738          "hidden": false,739          "trust_level": 1,740          "deleted_at": null,741          "user_deleted": false,742          "edit_reason": null,743          "can_view_edit_history": true,744          "wiki": false,745          "post_url": "/t/how-to-wait-on-non-blocking-copying-from-gpu-to-cpu/157010/1",746          "can_accept_answer": false,747          "can_unaccept_answer": false,748          "accepted_answer": false,749          "topic_accepted_answer": true,750          "can_vote": false751        },752        {753          "id": 357266,754          "name": "",755          "username": "ptrblck",756          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",757          "created_at": "2022-07-19T20:50:42.301Z",758          "cooked": "<p>Which PyTorch version are you using as I cannot reproduce it in the latest release?</p>",759          "post_number": 2,760          "post_type": 1,761          "posts_count": 5,762          "updated_at": "2022-07-19T20:50:42.301Z",763          "reply_count": 1,764          "reply_to_post_number": null,765          "quote_count": 0,766          "incoming_link_count": 17,767          "reads": 65,768          "readers_count": 64,769          "score": 103.0,770          "yours": false,771          "topic_id": 157010,772          "topic_slug": "how-to-wait-on-non-blocking-copying-from-gpu-to-cpu",773          "display_username": "",774          "primary_group_name": null,775          "flair_name": null,776          "flair_url": null,777          "flair_bg_color": null,778          "flair_color": null,779          "flair_group_id": null,780          "badges_granted": [],781          "version": 1,782          "can_edit": false,783          "can_delete": false,784          "can_recover": false,785          "can_see_hidden_post": false,786          "can_wiki": false,787          "read": true,788          "user_title": "",789          "bookmarked": false,790          "actions_summary": [],791          "moderator": true,792          "admin": true,793          "staff": true,794          "user_id": 3534,795          "hidden": false,796          "trust_level": 2,797          "deleted_at": null,798          "user_deleted": false,799          "edit_reason": null,800          "can_view_edit_history": true,801          "wiki": false,802          "post_url": "/t/how-to-wait-on-non-blocking-copying-from-gpu-to-cpu/157010/2",803          "can_accept_answer": false,804          "can_unaccept_answer": false,805          "accepted_answer": false,806          "topic_accepted_answer": true807        },808        {809          "id": 357307,810          "name": "Apprehensive Oil 284",811          "username": "Apprehensive-oil-284",812          "avatar_template": "/user_avatar/discuss.pytorch.org/apprehensive-oil-284/{size}/51596_2.png",813          "created_at": "2022-07-20T03:08:13.879Z",814          "cooked": "<p>maybe that’s because I have my GPU on a slow PCIE x4 link, and thus slowing down the transmission. Maybe you can increase the size of x?</p>\n<p>I’m using 1.12</p>",815          "post_number": 3,816          "post_type": 1,817          "posts_count": 5,818          "updated_at": "2022-07-20T03:08:13.879Z",819          "reply_count": 1,820          "reply_to_post_number": 2,821          "quote_count": 0,822          "incoming_link_count": 33,823          "reads": 68,824          "readers_count": 67,825          "score": 183.6,826          "yours": false,827          "topic_id": 157010,828          "topic_slug": "how-to-wait-on-non-blocking-copying-from-gpu-to-cpu",829          "display_username": "Apprehensive Oil 284",830          "primary_group_name": null,831          "flair_name": null,832          "flair_url": null,833          "flair_bg_color": null,834          "flair_color": null,835          "flair_group_id": null,836          "badges_granted": [],837          "version": 1,838          "can_edit": false,839          "can_delete": false,840          "can_recover": false,841          "can_see_hidden_post": false,842          "can_wiki": false,843          "read": true,844          "user_title": null,845          "reply_to_user": {846            "id": 3534,847            "username": "ptrblck",848            "name": "",849            "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png"850          },851          "bookmarked": false,852          "actions_summary": [],853          "moderator": false,854          "admin": false,855          "staff": false,856          "user_id": 57802,857          "hidden": false,858          "trust_level": 1,859          "deleted_at": null,860          "user_deleted": false,861          "edit_reason": null,862          "can_view_edit_history": true,863          "wiki": false,864          "post_url": "/t/how-to-wait-on-non-blocking-copying-from-gpu-to-cpu/157010/3",865          "can_accept_answer": false,866          "can_unaccept_answer": false,867          "accepted_answer": false,868          "topic_accepted_answer": true869        },870        {871          "id": 357322,872          "name": "",873          "username": "ptrblck",874          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",875          "created_at": "2022-07-20T05:05:00.289Z",876          "cooked": "<p>Yes, you are right and you would need to synchronize the current stream e.g. via:</p>\n<pre><code class=\"lang-python\">if __name__ == '__main__':\n    seed = 0\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    torch.cuda.manual_seed_all(seed)\n    \n    stream = torch.cuda.current_stream()\n\n    x = torch.rand(32, 256, 220, 220).cuda()\n\n    t = (x.min() - x.max()).to(torch.device(\"cpu\"), non_blocking=True)\n    print(stream.query()) # False - work not done yet\n    stream.synchronize() # wait for stream to finish the work\n    print(t)\n    \n    time.sleep(2.)\n    print(stream.query()) # True - work done\n    print(t)\n</code></pre>",877          "post_number": 4,878          "post_type": 1,879          "posts_count": 5,880          "updated_at": "2022-07-20T05:05:00.289Z",881          "reply_count": 0,882          "reply_to_post_number": 3,883          "quote_count": 0,884          "incoming_link_count": 67,885          "reads": 67,886          "readers_count": 66,887          "score": 378.4,888          "yours": false,889          "topic_id": 157010,890          "topic_slug": "how-to-wait-on-non-blocking-copying-from-gpu-to-cpu",891          "display_username": "",892          "primary_group_name": null,893          "flair_name": null,894          "flair_url": null,895          "flair_bg_color": null,896          "flair_color": null,897          "flair_group_id": null,898          "badges_granted": [],899          "version": 1,900          "can_edit": false,901          "can_delete": false,902          "can_recover": false,903          "can_see_hidden_post": false,904          "can_wiki": false,905          "link_counts": [906            {907              "url": "https://discuss.pytorch.org/t/should-we-set-non-blocking-to-true/38234/27",908              "internal": true,909              "reflection": true,910              "title": "Should we set non_blocking to True?",911              "clicks": 12912            }913          ],914          "read": true,915          "user_title": "",916          "reply_to_user": {917            "id": 57802,918            "username": "Apprehensive-oil-284",919            "name": "Apprehensive Oil 284",920            "avatar_template": "/user_avatar/discuss.pytorch.org/apprehensive-oil-284/{size}/51596_2.png"921          },922          "bookmarked": false,923          "actions_summary": [924            {925              "id": 2,926              "count": 2927            }928          ],929          "moderator": true,930          "admin": true,931          "staff": true,932          "user_id": 3534,933          "hidden": false,934          "trust_level": 2,935          "deleted_at": null,936          "user_deleted": false,937          "edit_reason": null,938          "can_view_edit_history": true,939          "wiki": false,940          "post_url": "/t/how-to-wait-on-non-blocking-copying-from-gpu-to-cpu/157010/4",941          "can_accept_answer": false,942          "can_unaccept_answer": false,943          "accepted_answer": true,944          "topic_accepted_answer": true945        },946        {947          "id": 357331,948          "name": "Apprehensive Oil 284",949          "username": "Apprehensive-oil-284",950          "avatar_template": "/user_avatar/discuss.pytorch.org/apprehensive-oil-284/{size}/51596_2.png",951          "created_at": "2022-07-20T05:57:27.371Z",952          "cooked": "<p>Thank you. Yes for the record, here is another example that uses cuda events:</p>\n<pre><code class=\"lang-auto\">import time\n\nimport torch\n\nclass Timer:\n    def __init__(self):\n        self.start = time.monotonic()\n\n    def __call__(self):\n        k = time.monotonic()\n        v = k - self.start\n        self.start = k\n        return v\n\nif __name__ == '__main__':\n\n\n    seed = 0\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    torch.cuda.manual_seed_all(seed)\n\n    stream = torch.cuda.Stream()\n\n    with torch.cuda.stream(stream):\n        # print(torch.cuda.current_stream())\n\n        x = torch.ones((32, 256, 220, 220), pin_memory=True)\n        tim = Timer()                \n        c = torch.empty((2, 32, 256, 220, 220), device='cuda')\n        print(tim())\n        # x = x.to(torch.device('cuda'), non_blocking=True)\n        print(tim())\n        c[0, :, :, :, :].copy_(x, non_blocking=True)\n        print(tim())\n\n        # t = (x.min() - x.max()).to(torch.device(\"cpu\"), non_blocking=True)\n\n        t = c[0].min()\n        print('mark0', tim())\n        t = t.to('cpu', non_blocking=True)\n        print('mark', tim())\n        ev = torch.cuda.Event()\n        ev.record()\n    # print(torch.cuda.current_stream())\n    print(tim())\n    print(t)\n    ev.synchronize()\n    print(tim())\n    print(t)\n</code></pre>\n<p>You will observe that only the last operation <code>ev.synchronize</code> takes substantial amount of time. All other operations are almost instant.</p>",953          "post_number": 5,954          "post_type": 1,955          "posts_count": 5,956          "updated_at": "2022-07-20T05:57:27.371Z",957          "reply_count": 0,958          "reply_to_post_number": null,959          "quote_count": 0,960          "incoming_link_count": 44,961          "reads": 64,962          "readers_count": 63,963          "score": 247.8,964          "yours": false,965          "topic_id": 157010,966          "topic_slug": "how-to-wait-on-non-blocking-copying-from-gpu-to-cpu",967          "display_username": "Apprehensive Oil 284",968          "primary_group_name": null,969          "flair_name": null,970          "flair_url": null,971          "flair_bg_color": null,972          "flair_color": null,973          "flair_group_id": null,974          "badges_granted": [],975          "version": 1,976          "can_edit": false,977          "can_delete": false,978          "can_recover": false,979          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