CoolFace
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Anurag1734/cuda-error-resolution-analysis

sourceHugging Faceupdated 2mo agoView on Hugging Face
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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 113463,7          "name": "",8          "username": "Shotare",9          "avatar_template": "/user_avatar/discuss.pytorch.org/shotare/{size}/12489_2.png",10          "created_at": "2019-05-26T17:27:50.050Z",11          "cooked": "<p>Hi!</p>\n<p>I am working on clothing detection and instead of k-nearest neighbours I decided to learn how neural networks work. So I created very simple network and started to train it based on a tutorial: <a href=\"https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html\" rel=\"nofollow noopener\">https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html</a></p>\n<p>At first it looked very primising. The loss was decreasing in a satisfying rate, but it stopped as quickly as it started.<br>\nAs I am at beginner in neural networks I don’t know what to do to imporve my neural network now.</p>\n<p>Here is the code:</p>\n<pre><code class=\"lang-auto\">import torchvision\nimport torchvision.transforms as transforms\nimport torch\nfrom torch import nn\nimport torch.optim as optim\nimport pickle as pkl\n\n\nif __name__ == '__main__':\n\n    device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n\n    data = pkl.load(open('train.pkl', mode='rb'))\n    traindata = data[0]\n    labels = data[1]\n    tensor_data = torch.stack([torch.Tensor(i) for i in traindata])\n    tensor_labels = torch.from_numpy(labels)\n\n    dataset = torch.utils.data.TensorDataset(tensor_data, tensor_labels)\n\n    trainloader = torch.utils.data.DataLoader(dataset, batch_size=16,\n                                              shuffle=True, num_workers=2)\n    testloader = torch.utils.data.DataLoader(dataset, batch_size=16,\n                                             shuffle=False, num_workers=2)\n\n    torch.multiprocessing.freeze_support()\n\n\n    class SimpleNetwork(nn.Module):\n        def __init__(self):\n            super(SimpleNetwork, self).__init__()\n            self.fc1 = nn.Linear(1296, 10)\n            self.sig = nn.Sigmoid()\n            self.params = list(self.fc1.parameters())\n\n        def forward(self, x):\n            x = self.fc1(x)\n            x = self.sig(x)\n            return x\n\n        def get_params(self):\n            w = self.params\n            return w\n\n\n    net = SimpleNetwork()\n    #net.to(device)\n    criterion = nn.CrossEntropyLoss()\n    optimizer = optim.SGD(net.parameters(), lr=0.01, momentum=0.9)\n\n    print('testing started')\n\n    for epoch in range(20):\n        net.load_state_dict(torch.load('parameters.pkl'))\n        net.eval()\n        running_loss = 0.0\n        for i, data in enumerate(trainloader, 0):\n            inputs, labels = data\n            #inputs, labels = inputs.to(device), labels.to(device)\n\n            optimizer.zero_grad()\n\n            outputs = net(inputs)\n            loss = criterion(outputs, labels)\n            loss.backward()\n            optimizer.step()\n            #print(torch.sum(net.fc1.weight.data))\n\n            running_loss += loss.item()\n            if i % 2000 == 1999:\n                print('[%d, %5d] loss: %.3f' %\n                      (epoch + 1, i + 1, running_loss / 2000))\n                running_loss = 0.0\n\n    data = net.fc1.weight.data.numpy(), net.fc1.bias.data.numpy()\n    with open('weights.pkl', 'wb') as f:\n        pkl.dump(data, f)\n\n    torch.save(net.state_dict(), 'parameters.pkl')\n    print('finished testing')\n\n\n</code></pre>\n<p>My data (train.pkl) is a file containing a numpy array of images (represented as 1296 floats) and a array of labels (from 0 to 9)<br>\nI need to extract weights from this model, hence last few lines of code</p>\n<p>What can I do make this neural network learn?<br>\nPlease help</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 4,15          "updated_at": "2019-05-26T17:27:50.050Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 1430,20          "reads": 59,21          "readers_count": 58,22          "score": 7161.8,23          "yours": false,24          "topic_id": 46257,25          "topic_slug": "my-very-first-neural-network-doesnt-seem-to-learn",26          "display_username": "",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          "link_counts": [41            {42              "url": "https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html",43              "internal": false,44              "reflection": false,45              "title": "Training a Classifier — PyTorch Tutorials 1.1.0 documentation",46              "clicks": 947            }48          ],49          "read": true,50          "user_title": null,51          "bookmarked": false,52          "actions_summary": [],53          "moderator": false,54          "admin": false,55          "staff": false,56          "user_id": 19025,57          "hidden": false,58          "trust_level": 0,59          "deleted_at": null,60          "user_deleted": false,61          "edit_reason": null,62          "can_view_edit_history": true,63          "wiki": false,64          "post_url": "/t/my-very-first-neural-network-doesnt-seem-to-learn/46257/1",65          "can_accept_answer": false,66          "can_unaccept_answer": false,67          "accepted_answer": false,68          "topic_accepted_answer": null,69          "can_vote": false70        },71        {72          "id": 113465,73          "name": "",74          "username": "ptrblck",75          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",76          "created_at": "2019-05-26T20:04:03.082Z",77          "cooked": "<p><code>nn.CrossEntropyLoss</code> expects logits as the model output. Remove the sigmoid operation on the output tensor in your model and try to run your code again.</p>",78          "post_number": 2,79          "post_type": 1,80          "posts_count": 4,81          "updated_at": "2019-05-26T20:04:03.082Z",82          "reply_count": 1,83          "reply_to_post_number": null,84          "quote_count": 0,85          "incoming_link_count": 7,86          "reads": 49,87          "readers_count": 48,88          "score": 49.8,89          "yours": false,90          "topic_id": 46257,91          "topic_slug": "my-very-first-neural-network-doesnt-seem-to-learn",92          "display_username": "",93          "primary_group_name": null,94          "flair_name": null,95          "flair_url": null,96          "flair_bg_color": null,97          "flair_color": null,98          "flair_group_id": null,99          "badges_granted": [],100          "version": 1,101          "can_edit": false,102          "can_delete": false,103          "can_recover": false,104          "can_see_hidden_post": false,105          "can_wiki": false,106          "read": true,107          "user_title": "",108          "bookmarked": false,109          "actions_summary": [],110          "moderator": true,111          "admin": true,112          "staff": true,113          "user_id": 3534,114          "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/my-very-first-neural-network-doesnt-seem-to-learn/46257/2",122          "can_accept_answer": false,123          "can_unaccept_answer": false,124          "accepted_answer": false,125          "topic_accepted_answer": null126        },127        {128          "id": 113554,129          "name": "",130          "username": "Shotare",131          "avatar_template": "/user_avatar/discuss.pytorch.org/shotare/{size}/12489_2.png",132          "created_at": "2019-05-27T10:56:31.814Z",133          "cooked": "<p>It made things even worse - the loss got bigger and didn’t decrease over epochs</p>",134          "post_number": 3,135          "post_type": 1,136          "posts_count": 4,137          "updated_at": "2019-05-27T10:56:31.814Z",138          "reply_count": 1,139          "reply_to_post_number": 2,140          "quote_count": 0,141          "incoming_link_count": 2,142          "reads": 49,143          "readers_count": 48,144          "score": 24.8,145          "yours": false,146          "topic_id": 46257,147          "topic_slug": "my-very-first-neural-network-doesnt-seem-to-learn",148          "display_username": "",149          "primary_group_name": null,150          "flair_name": null,151          "flair_url": null,152          "flair_bg_color": null,153          "flair_color": null,154          "flair_group_id": null,155          "badges_granted": [],156          "version": 1,157          "can_edit": false,158          "can_delete": false,159          "can_recover": false,160          "can_see_hidden_post": false,161          "can_wiki": false,162          "read": true,163          "user_title": null,164          "reply_to_user": {165            "id": 3534,166            "username": "ptrblck",167            "name": "",168            "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png"169          },170          "bookmarked": false,171          "actions_summary": [],172          "moderator": false,173          "admin": false,174          "staff": false,175          "user_id": 19025,176          "hidden": false,177          "trust_level": 0,178          "deleted_at": null,179          "user_deleted": false,180          "edit_reason": null,181          "can_view_edit_history": true,182          "wiki": false,183          "post_url": "/t/my-very-first-neural-network-doesnt-seem-to-learn/46257/3",184          "can_accept_answer": false,185          "can_unaccept_answer": false,186          "accepted_answer": false,187          "topic_accepted_answer": null188        },189        {190          "id": 113556,191          "name": "",192          "username": "ptrblck",193          "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",194          "created_at": "2019-05-27T10:59:01.085Z",195          "cooked": "<p>That souldn’t be the case. Could you add a hidden layer with a non-linearity to your model, and change some hyper-parameters, e.g. lower the learning rate?</p>",196          "post_number": 4,197          "post_type": 1,198          "posts_count": 4,199          "updated_at": "2019-05-27T10:59:01.085Z",200          "reply_count": 0,201          "reply_to_post_number": 3,202          "quote_count": 0,203          "incoming_link_count": 10,204          "reads": 48,205          "readers_count": 47,206          "score": 74.6,207          "yours": false,208          "topic_id": 46257,209          "topic_slug": "my-very-first-neural-network-doesnt-seem-to-learn",210          "display_username": "",211          "primary_group_name": null,212          "flair_name": null,213          "flair_url": null,214          "flair_bg_color": null,215          "flair_color": null,216          "flair_group_id": null,217          "badges_granted": [],218          "version": 1,219          "can_edit": false,220          "can_delete": 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"/user_avatar/discuss.pytorch.org/lxtgh/{size}/3711_2.png"1063      }1064    },1065    "bookmarks": []1066  },1067  {1068    "post_stream": {1069      "posts": [1070        {1071          "id": 113516,1072          "name": "Caiwenpu",1073          "username": "caiwenpu",1074          "avatar_template": "/user_avatar/discuss.pytorch.org/caiwenpu/{size}/27138_2.png",1075          "created_at": "2019-05-27T06:46:54.848Z",1076          "cooked": "<pre><code class=\"lang-auto\">torch.manual_seed(0)\nW = torch.FloatTensor(10, 5000).normal_(0,1)\n\nprint(W.norm(2) ** 2, W.sum())\nW = W.cuda()\n\nprint(W.norm(2) ** 2, W.sum())\n\nW = W.cpu()\nprint(W.norm(2) ** 2, W.sum())\n</code></pre>\n<p>When I run this code, the results is</p>\n<pre><code class=\"lang-auto\">tensor(97479.4609) tensor(-358.1119)\ntensor(50004.2148, device='cuda:0') tensor(-358.1118, device='cuda:0')\ntensor(97479.4609) tensor(-358.1119)\n</code></pre>\n<p>The results of norm is significantly different, but the results of sum is almost the same.<br>\nWhen I change the size of tensor W from (10,5000) to (10,1000). I get the results:</p>\n<pre><code class=\"lang-auto\">tensor(10038.8496) tensor(-106.9817)\ntensor(10038.8516, device='cuda:0') tensor(-106.9818, device='cuda:0')\ntensor(10038.8496) tensor(-106.9817)\n</code></pre>\n<p>The results of norm is almost the same.<br>\nI want to figure out how to explain these results?</p>",1077          "post_number": 1,1078          "post_type": 1,1079          "posts_count": 4,1080          "updated_at": "2019-05-27T06:57:37.416Z",1081          "reply_count": 0,1082          "reply_to_post_number": null,1083          "quote_count": 0,1084          "incoming_link_count": 237,1085          "reads": 16,1086          "readers_count": 15,1087          "score": 1183.2,1088          "yours": false,1089          "topic_id": 46288,1090          "topic_slug": "cpu-and-gpu-tensor-norm-different",1091          "display_username": "Caiwenpu",1092          "primary_group_name": null,1093          "flair_name": null,1094          "flair_url": null,1095          "flair_bg_color": null,1096          "flair_color": null,1097          "flair_group_id": null,1098          "badges_granted": [],1099          "version": 2,1100          "can_edit": false,1101          "can_delete": false,1102          "can_recover": false,1103          "can_see_hidden_post": false,1104          "can_wiki": false,1105          "read": true,1106          "user_title": null,1107          "bookmarked": false,1108          "actions_summary": [],1109          "moderator": false,1110          "admin": false,1111          "staff": false,1112          "user_id": 19036,1113          "hidden": false,1114          "trust_level": 1,1115          "deleted_at": null,1116          "user_deleted": false,1117          "edit_reason": null,1118          "can_view_edit_history": true,1119          "wiki": false,1120          "post_url": "/t/cpu-and-gpu-tensor-norm-different/46288/1",1121          "can_accept_answer": false,1122          "can_unaccept_answer": false,1123          "accepted_answer": false,1124          "topic_accepted_answer": null,1125          "can_vote": false1126        },1127        {1128          "id": 113519,1129          "name": "Atsushi SAKAI",1130          "username": "sakaia",1131          "avatar_template": "/user_avatar/discuss.pytorch.org/sakaia/{size}/5205_2.png",1132          "created_at": "2019-05-27T07:19:00.109Z",1133          "cooked": "<p>Interesting results! But I try to do it on Google Colab, the problem occured on large tensor.</p>\n<pre><code class=\"lang-auto\">import torch\ntorch.manual_seed(0)\nW = torch.FloatTensor(100, 5000000).normal_(0,1)\n\nprint(W.norm(2) ** 2, W.sum())\nW = W.cuda()\n\nprint(W.norm(2) ** 2, W.sum())\n\nW = W.cpu()\nprint(W.norm(2) ** 2, W.sum())\n!nvidia-smi\n</code></pre>\n<pre><code class=\"lang-auto\">tensor(1.5166e+08) tensor(-34600.6719)\ntensor(5.0001e+08, device='cuda:0') tensor(-34600.1719, device='cuda:0')\ntensor(1.5166e+08) tensor(-34600.6719)\nMon May 27 07:17:41 2019       \n+-----------------------------------------------------------------------------+\n| NVIDIA-SMI 418.67       Driver Version: 410.79       CUDA Version: 10.0     |\n|-------------------------------+----------------------+----------------------+\n| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n|===============================+======================+======================|\n|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n| N/A   71C    P0    31W /  70W |   3244MiB / 15079MiB |      0%      Default |\n+-------------------------------+----------------------+----------------------+\n</code></pre>",1134          "post_number": 2,1135          "post_type": 1,1136          "posts_count": 4,1137          "updated_at": "2019-05-27T07:19:00.109Z",1138          "reply_count": 1,1139          "reply_to_post_number": null,1140          "quote_count": 0,1141          "incoming_link_count": 3,1142          "reads": 15,1143          "readers_count": 14,1144          "score": 23.0,1145          "yours": false,1146          "topic_id": 46288,1147          "topic_slug": "cpu-and-gpu-tensor-norm-different",1148          "display_username": "Atsushi SAKAI",1149          "primary_group_name": null,1150          "flair_name": null,1151          "flair_url": null,1152          "flair_bg_color": null,1153          "flair_color": null,1154          "flair_group_id": null,1155          "badges_granted": [],1156          "version": 1,1157          "can_edit": false,1158          "can_delete": false,1159          "can_recover": false,1160          "can_see_hidden_post": false,1161          "can_wiki": false,1162          "read": true,1163          "user_title": null,1164          "bookmarked": false,1165          "actions_summary": [],1166          "moderator": false,1167          "admin": false,1168          "staff": false,1169          "user_id": 9135,1170          "hidden": false,1171          "trust_level": 2,1172          "deleted_at": null,1173          "user_deleted": false,1174          "edit_reason": null,1175          "can_view_edit_history": true,1176          "wiki": false,1177          "post_url": "/t/cpu-and-gpu-tensor-norm-different/46288/2",1178          "can_accept_answer": false,1179          "can_unaccept_answer": false,1180          "accepted_answer": false,1181          "topic_accepted_answer": null1182        },1183        {1184          "id": 113527,1185          "name": "Atsushi SAKAI",1186          "username": "sakaia",1187          "avatar_template": "/user_avatar/discuss.pytorch.org/sakaia/{size}/5205_2.png",1188          "created_at": "2019-05-27T07:42:19.234Z",1189          "cooked": "<p>It seems CPU side problem.</p>\n<pre><code class=\"lang-auto\">import torch\nHIGHT = 100\nWIDTH = 5000000\ntorch.manual_seed(0)\nW = torch.FloatTensor(HIGHT, WIDTH).normal_(0,1)\nWv = W.view(HIGHT*WIDTH,1)\nWTW = Wv * Wv\nprint(WTW.sum())\nprint(W.norm(2) ** 2, W.sum())\n\nW = W.cuda()\nWv = W.view(HIGHT*WIDTH,1)\nWTW = Wv * Wv\nprint(WTW.sum())\nprint(W.norm(2) ** 2, W.sum())\n\nW = W.cpu()\nprint(W.norm(2) ** 2, W.sum())\n!nvidia-smi\n</code></pre>\n<pre><code class=\"lang-auto\">tensor(4.8664e+08)\ntensor(1.5166e+08) tensor(-34600.6719)\ntensor(5.0001e+08, device='cuda:0')\ntensor(5.0001e+08, device='cuda:0') tensor(-34600.1719, device='cuda:0')\ntensor(1.5166e+08) tensor(-34600.6719)\nMon May 27 07:41:05 2019       \n+-----------------------------------------------------------------------------+\n| NVIDIA-SMI 418.67       Driver Version: 410.79       CUDA Version: 10.0     |\n|-------------------------------+----------------------+----------------------+\n| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n|===============================+======================+======================|\n|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n| N/A   70C    P0    31W /  70W |   5152MiB / 15079MiB |      0%      Default |\n+-------------------------------+----------------------+----------------------+\n</code></pre>",1190          "post_number": 3,1191          "post_type": 1,1192          "posts_count": 4,1193          "updated_at": "2019-05-27T07:42:19.234Z",1194          "reply_count": 1,1195          "reply_to_post_number": 2,1196          "quote_count": 0,1197          "incoming_link_count": 3,1198          "reads": 14,1199          "readers_count": 13,1200          "score": 22.8,

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