CoolFace
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Anurag1734/cuda-error-resolution-analysis

sourceHugging Faceupdated 2mo agoView on Hugging Face
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topics_batch_168.json64316 linesDownload Raw Back to raw
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"id": 384399,456          "name": "Chhatra Bikram",457          "username": "Chhatra",458          "avatar_template": "/letter_avatar_proxy/v4/letter/c/6de8d8/{size}.png",459          "created_at": "2023-01-24T11:04:53.337Z",460          "cooked": "<p>Hello people ,<br>\nsorry to bother you guys but I am just getting started implementing some complex begginner friendly projects with pytorch . So to code a sequence to sequence artitecture with pytorch. I thought of coding a video captioning system . I have used kinematics dataset only about (1200) samples.<br>\nMy video captioning model predicts same caption for any video so I want help</p>\n<p>this is my colab file link<br>\n:<a href=\"https://colab.research.google.com/drive/1eeoDktRG0If4__X9DCuLpPwCCqCqMP4E\" class=\"inline-onebox\" rel=\"noopener nofollow ugc\">Google Colab</a><br>\nplease help</p>\n<p>I think there is problem in my training loop</p>",461          "post_number": 1,462          "post_type": 1,463          "posts_count": 3,464          "updated_at": "2023-01-24T11:04:53.337Z",465          "reply_count": 0,466          "reply_to_post_number": null,467          "quote_count": 0,468          "incoming_link_count": 82,469          "reads": 5,470          "readers_count": 4,471          "score": 411.0,472          "yours": false,473          "topic_id": 170960,474          "topic_slug": 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"created_at": "2023-01-25T01:36:49.769Z",526          "cooked": "<p>It seems you are using <code>nn.CrossEntropyLoss</code>, which expects raw logits as the model output, while you are applying a <code>softmax</code> on the decoder’s <code>output</code> tensor thus creating probabilities.<br>\nRemove the <code>softmax</code> and see if this would help training the model.</p>",527          "post_number": 2,528          "post_type": 1,529          "posts_count": 3,530          "updated_at": "2023-01-25T01:36:49.769Z",531          "reply_count": 0,532          "reply_to_post_number": null,533          "quote_count": 0,534          "incoming_link_count": 1,535          "reads": 5,536          "readers_count": 4,537          "score": 6.0,538          "yours": false,539          "topic_id": 170960,540          "topic_slug": "model-giving-same-output-for-all-video-while-creating-a-pytorch-video-captioning-system-using-gru-encoder-and-gru-language-decoder",541          "display_username": 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"/t/model-giving-same-output-for-all-video-while-creating-a-pytorch-video-captioning-system-using-gru-encoder-and-gru-language-decoder/170960/2",571          "can_accept_answer": false,572          "can_unaccept_answer": false,573          "accepted_answer": false,574          "topic_accepted_answer": null575        },576        {577          "id": 384583,578          "name": "Chhatra Bikram",579          "username": "Chhatra",580          "avatar_template": "/letter_avatar_proxy/v4/letter/c/6de8d8/{size}.png",581          "created_at": "2023-01-25T09:33:13.744Z",582          "cooked": "<p>I removed the softmax function but it doesnot help in training My model still classifying same text for all videos.  Actually I have used this <a href=\"https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html\" class=\"inline-onebox\" rel=\"noopener nofollow ugc\">NLP From Scratch: Translation with a Sequence to Sequence Network and Attention — PyTorch Tutorials 1.13.1+cu117 documentation</a><br>\ntutorial and modified encoder layer to take video as input instead of sentence and modified code little to use accelerator , rest other things are same. I tried both attention decoder and simple decoder given in this tutorial still I got same result. My model is not learning , the loss plot is random up and down.</p>",583          "post_number": 3,584          "post_type": 1,585          "posts_count": 3,586          "updated_at": "2023-01-25T09:33:13.744Z",587          "reply_count": 0,588          "reply_to_post_number": null,589          "quote_count": 0,590          "incoming_link_count": 1,591          "reads": 4,592          "readers_count": 3,593          "score": 5.8,594          "yours": false,595          "topic_id": 170960,596          "topic_slug": "model-giving-same-output-for-all-video-while-creating-a-pytorch-video-captioning-system-using-gru-encoder-and-gru-language-decoder",597          "display_username": "Chhatra Bikram",598          "primary_group_name": null,599          "flair_name": null,600          "flair_url": null,601          "flair_bg_color": null,602          "flair_color": null,603          "flair_group_id": null,604          "badges_granted": [],605          "version": 1,606          "can_edit": 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FocalLoss(nn.Module):</p>\n<pre><code>def __init__(self, weight=None, \n             gamma=2., reduction='none'):\n    nn.Module.__init__(self)\n    self.weight = weight\n    self.gamma = gamma\n    self.reduction = reduction\n    \ndef forward(self, input_tensor, target_tensor):\n    target_tensor = torch.argmax(target_tensor ,axis=1)\n    log_prob = F.log_softmax(input_tensor, dim=-1)\n    prob = torch.exp(log_prob)\n    return F.nll_loss(\n        ((1 - prob) ** self.gamma) * log_prob, \n        target_tensor, \n        weight=self.weight,\n        reduction = self.reduction\n    )\n</code></pre>\n<p>—&gt; 33             batch_loss += loss.item()<br>\n34             total_loss += loss.item()<br>\n35</p>\n<p>ValueError: only one element tensors can be converted to Python scalars</p>",1073          "post_number": 1,1074          "post_type": 1,1075          "posts_count": 3,1076          "updated_at": "2023-01-23T10:39:47.345Z",1077          "reply_count": 1,1078          "reply_to_post_number": null,1079          "quote_count": 0,1080          "incoming_link_count": 696,1081          "reads": 15,1082          "readers_count": 14,1083          "score": 3483.0,1084          "yours": false,1085          "topic_id": 170880,1086          "topic_slug": "in-loss-item-getting-error-valueerror-only-one-element-tensors-can-be-converted-to-python-scalars",1087          "display_username": "Garry Santana",1088          "primary_group_name": null,1089          "flair_name": null,1090          "flair_url": null,1091          "flair_bg_color": null,1092          "flair_color": null,1093          "flair_group_id": null,1094          "badges_granted": [],1095          "version": 1,1096          "can_edit": false,1097          "can_delete": false,1098          "can_recover": false,1099          "can_see_hidden_post": false,1100          "can_wiki": false,1101          "read": true,1102          "user_title": null,1103          "bookmarked": false,1104          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Frank",1126          "username": "KFrank",1127          "avatar_template": "/letter_avatar_proxy/v4/letter/k/ecb155/{size}.png",1128          "created_at": "2023-01-23T20:56:54.765Z",1129          "cooked": "<p>Hi Garry!</p>\n<aside class=\"quote no-group quote-modified\" data-username=\"Garry_Santana\" data-post=\"1\" data-topic=\"170880\" data-full=\"true\">\n<div class=\"title\">\n<div class=\"quote-controls\"></div>\n<img loading=\"lazy\" alt=\"\" width=\"24\" height=\"24\" src=\"https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/garry_santana/48/56660_2.png\" class=\"avatar\"> Garry_Santana:</div>\n<blockquote>\n<pre><code>def __init__(self, weight=None, \n             gamma=2., reduction='none'):\n</code></pre>\n<p>…<br>\nreturn F.nll_loss(<br>\n((1 - prob) ** self.gamma) * log_prob,<br>\ntarget_tensor,<br>\nweight=self.weight,<br>\nreduction = self.reduction<br>\n)</p>\n<p>—&gt; 33             batch_loss += loss.item()</p>\n<p>ValueError: only one element tensors can be converted to Python scalars</p>\n</blockquote>\n</aside>\n<p>Because you use <code>reduction = 'none'</code> in <code>nll_loss()</code>, it will (most likely)<br>\nreturn a batch of loss values and therefore <code>loss</code> will be a tensor that<br>\ncontains more than one element.</p>\n<p>The purpose of <code>.item()</code> is to convert a <em>single-element</em> tensor into a regular<br>\npython scalar, hence the error.  Try using <code>reduction = 'mean'</code> (the default)<br>\nand <code>loss</code> should now be a single-element tensor for which <code>.item()</code> will work.</p>\n<p>Best.</p>\n<p>K. Frank</p>",1130          "post_number": 2,1131          "post_type": 1,1132          "posts_count": 3,1133          "updated_at": "2023-01-23T20:56:54.765Z",1134          "reply_count": 1,1135          "reply_to_post_number": null,1136          "quote_count": 1,1137          "incoming_link_count": 11,1138          "reads": 11,1139          "readers_count": 10,1140          "score": 62.2,1141          "yours": false,1142          "topic_id": 170880,1143          "topic_slug": "in-loss-item-getting-error-valueerror-only-one-element-tensors-can-be-converted-to-python-scalars",1144          "display_username": "K. Frank",1145          "primary_group_name": null,1146          "flair_name": null,1147          "flair_url": null,1148          "flair_bg_color": null,1149          "flair_color": null,1150          "flair_group_id": null,1151          "badges_granted": [],1152          "version": 1,1153          "can_edit": false,1154          "can_delete": false,1155          "can_recover": false,1156          "can_see_hidden_post": false,1157          "can_wiki": false,1158          "read": true,1159          "user_title": null,1160          "bookmarked": false,1161          "actions_summary": [],1162          "moderator": false,1163          "admin": false,1164          "staff": false,1165          "user_id": 18088,1166          "hidden": false,1167          "trust_level": 2,1168          "deleted_at": null,1169          "user_deleted": false,1170          "edit_reason": null,1171          "can_view_edit_history": true,1172          "wiki": false,1173          "post_url": "/t/in-loss-item-getting-error-valueerror-only-one-element-tensors-can-be-converted-to-python-scalars/170880/2",1174          "can_accept_answer": false,1175          "can_unaccept_answer": false,1176          "accepted_answer": true,1177          "topic_accepted_answer": true1178        },1179        {1180          "id": 384577,1181          "name": "Garry Santana",1182          "username": "Garry_Santana",1183          "avatar_template": "/user_avatar/discuss.pytorch.org/garry_santana/{size}/56660_2.png",1184          "created_at": "2023-01-25T09:02:03.476Z",1185          "cooked": "<p>Thank you very much, Frank that fixed my problem!</p>",1186          "post_number": 3,1187          "post_type": 1,1188          "posts_count": 3,1189          "updated_at": "2023-01-25T09:02:03.476Z",1190          "reply_count": 0,1191          "reply_to_post_number": 2,1192          "quote_count": 0,1193          "incoming_link_count": 3,1194          "reads": 7,1195          "readers_count": 6,1196          "score": 16.4,1197          "yours": false,1198          "topic_id": 170880,1199          "topic_slug": "in-loss-item-getting-error-valueerror-only-one-element-tensors-can-be-converted-to-python-scalars",1200          "display_username": "Garry Santana",

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