Anurag1734/cuda-error-resolution-analysis
07
1[2 {3 "post_stream": {4 "posts": [5 {6 "id": 258225,7 "name": "shuangkang fang",8 "username": "Fangkang515",9 "avatar_template": "/user_avatar/discuss.pytorch.org/fangkang515/{size}/33626_2.png",10 "created_at": "2021-01-20T08:11:56.028Z",11 "cooked": "<p>The loss is always Nan when I use the loss function as follow:</p>\n<pre><code class=\"lang-auto\">def Myloss1(source, target):\n loss = torch.nn.functional.mse_loss(source, target, reduction=\"none\")\n return torch.sum(loss).sqrt()\n\n...\n\nloss = Myloss1(s, t)\nloss.backward()\n\n</code></pre>\n<br>\n<p>But when I use the following loss function, the training becomes normal:</p>\n<pre><code class=\"lang-auto\">def Myloss2(source, target):\n diff = target - source\n loss = torch.norm(diff)\n return loss\n...\n\nloss = Myloss2(s, t)\nloss.backward()\n\n</code></pre>\n<br>\n<p>Why can’t use the ‘Myloss1’ to train？ Aren’t Myloss1 and Myloss2 equivalent?</p>\n<p>Please help me，thank you very much！</p>",12 "post_number": 1,13 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Later the network should work online so that every input state is classified.</p>\n<p>(1): Now, for training I could give a sliding window with the last n timesteps as input (n high enough/suitable for the task of course) and use the last output for the classification of the last time step (many-to-one)</p>\n<p>(2): I could also give a big sequence and use every output to classify every timestep in this sequence (many-to-many)</p>\n<p>Which is the better way to do it? In (1) I got for every timestep the same length of previous information. In (2), can I use a sliding window? 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Frank",775 "avatar_template": "/letter_avatar_proxy/v4/letter/k/ecb155/{size}.png",776 "trust_level": 2777 }778 }779 ]780 }781 ],782 "tags_descriptions": {},783 "fancy_title": "Training LSTM Network as many-to-one or many-to-many",784 "id": 109403,785 "title": "Training LSTM Network as many-to-one or many-to-many",786 "posts_count": 1,787 "created_at": "2021-01-20T07:59:33.688Z",788 "views": 413,789 "reply_count": 0,790 "like_count": 0,791 "last_posted_at": "2021-01-20T07:59:33.750Z",792 "visible": true,793 "closed": false,794 "archived": false,795 "has_summary": false,796 "archetype": "regular",797 "slug": "training-lstm-network-as-many-to-one-or-many-to-many",798 "category_id": 1,799 "word_count": 153,800 "deleted_at": null,801 "user_id": 38182,802 "featured_link": null,803 "pinned_globally": false,804 "pinned_at": null,805 "pinned_until": null,806 "image_url": null,807 "slow_mode_seconds": 0,808 "draft": null,809 "draft_key": "topic_109403",810 "draft_sequence": null,811 "unpinned": null,812 "pinned": false,813 "current_post_number": 1,814 "highest_post_number": 1,815 "deleted_by": null,816 "actions_summary": [817 {818 "id": 4,819 "count": 0,820 "hidden": false,821 "can_act": false822 },823 {824 "id": 8,825 "count": 0,826 "hidden": false,827 "can_act": false828 },829 {830 "id": 10,831 "count": 0,832 "hidden": false,833 "can_act": false834 },835 {836 "id": 7,837 "count": 0,838 "hidden": false,839 "can_act": false840 }841 ],842 "chunk_size": 20,843 "bookmarked": false,844 "topic_timer": null,845 "message_bus_last_id": 0,846 "participant_count": 1,847 "show_read_indicator": false,848 "thumbnails": null,849 "slow_mode_enabled_until": null,850 "can_vote": false,851 "vote_count": 0,852 "user_voted": false,853 "discourse_zendesk_plugin_zendesk_id": null,854 "discourse_zendesk_plugin_zendesk_url": "https://your-url.zendesk.com/agent/tickets/",855 "details": {856 "can_edit": false,857 "notification_level": 1,858 "participants": [859 {860 "id": 38182,861 "username": "Johannes_L",862 "name": "",863 "avatar_template": "/user_avatar/discuss.pytorch.org/johannes_l/{size}/30296_2.png",864 "post_count": 1,865 "primary_group_name": null,866 "flair_name": null,867 "flair_url": null,868 "flair_color": null,869 "flair_bg_color": null,870 "flair_group_id": null,871 "trust_level": 1872 }873 ],874 "created_by": {875 "id": 38182,876 "username": "Johannes_L",877 "name": "",878 "avatar_template": "/user_avatar/discuss.pytorch.org/johannes_l/{size}/30296_2.png"879 },880 "last_poster": {881 "id": 38182,882 "username": "Johannes_L",883 "name": "",884 "avatar_template": "/user_avatar/discuss.pytorch.org/johannes_l/{size}/30296_2.png"885 }886 },887 "bookmarks": []888 },889 {890 "post_stream": {891 "posts": [892 {893 "id": 257879,894 "name": "",895 "username": "danielmanu93",896 "avatar_template": "/letter_avatar_proxy/v4/letter/d/a88e4f/{size}.png",897 "created_at": "2021-01-18T21:36:45.945Z",898 "cooked": "<p>Hi everyone, I am trying to train a graph neural network on a PPI dataset. The code below shows a part of a code that passes messages from neighboring nodes through connecting edges. I get Type error as shown in the image below when I run this code through an import from the main program. From the error message, the error is from line 83, specifically \"edge_index[idx] which returns a “none” instead of an element corresponding to an idx value in the array. But when I print the “idx”, it returns “1” so it should probably return index 1 element from the edge_index array but returns a “none” instead which throws an error. See attached the images.</p>\n<p><img src=\"https://discuss.pytorch.org/uploads/default/original/3X/e/a/ea39f9f7ccf74dd955c3ae6424e1f453e074acc0.jpeg\" alt=\"1\" data-base62-sha1=\"xq3Wp9XEy7I2N6Ms5yF0COSQE8M\" width=\"581\" height=\"414\"></p>\n<p><div class=\"lightbox-wrapper\"><a class=\"lightbox\" href=\"https://discuss.pytorch.org/uploads/default/original/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60.jpeg\" data-download-href=\"https://discuss.pytorch.org/uploads/default/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60\" title=\"2\"><img src=\"https://discuss.pytorch.org/uploads/default/optimized/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60_2_690x70.jpeg\" alt=\"2\" data-base62-sha1=\"gnIkJfzEunTIga2A30pOB1PlKx2\" width=\"690\" height=\"70\" srcset=\"https://discuss.pytorch.org/uploads/default/optimized/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60_2_690x70.jpeg, https://discuss.pytorch.org/uploads/default/original/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60.jpeg 2x\" data-dominant-color=\"313131\"><div class=\"meta\"><svg class=\"fa d-icon d-icon-far-image svg-icon\" aria-hidden=\"true\"><use href=\"#far-image\"></use></svg><span class=\"filename\">2</span><span class=\"informations\">721×74 26.5 KB</span><svg class=\"fa d-icon d-icon-discourse-expand svg-icon\" aria-hidden=\"true\"><use href=\"#discourse-expand\"></use></svg></div></a></div></p>",899 "post_number": 1,900 "post_type": 1,901 "posts_count": 6,902 "updated_at": "2021-01-18T21:39:02.703Z",903 "reply_count": 0,904 "reply_to_post_number": null,905 "quote_count": 0,906 "incoming_link_count": 1633,907 "reads": 16,908 "readers_count": 15,909 "score": 8163.2,910 "yours": false,911 "topic_id": 109239,912 "topic_slug": "typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out",913 "display_username": "",914 "primary_group_name": null,915 "flair_name": null,916 "flair_url": null,917 "flair_bg_color": null,918 "flair_color": null,919 "flair_group_id": null,920 "badges_granted": [],921 "version": 1,922 "can_edit": false,923 "can_delete": false,924 "can_recover": false,925 "can_see_hidden_post": false,926 "can_wiki": false,927 "link_counts": [928 {929 "url": "https://discuss.pytorch.org/uploads/default/original/3X/7/2/72d10e9c95f813c65de388edfb8d2e6b2bb3dd60.jpeg",930 "internal": true,931 "reflection": false,932 "clicks": 0933 }934 ],935 "read": true,936 "user_title": null,937 "bookmarked": false,938 "actions_summary": [],939 "moderator": false,940 "admin": false,941 "staff": false,942 "user_id": 40263,943 "hidden": false,944 "trust_level": 1,945 "deleted_at": null,946 "user_deleted": false,947 "edit_reason": null,948 "can_view_edit_history": true,949 "wiki": false,950 "post_url": "/t/typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out/109239/1",951 "can_accept_answer": false,952 "can_unaccept_answer": false,953 "accepted_answer": false,954 "topic_accepted_answer": null,955 "can_vote": false956 },957 {958 "id": 258174,959 "name": "",960 "username": "ptrblck",961 "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",962 "created_at": "2021-01-20T02:57:03.895Z",963 "cooked": "<p>What were the <code>print</code> statements returning in the iteration before this error is raised?<br>\nDid you make sure that <code>edge_index[idx]</code> returned a valid tensor? If so, could you post an executable code snippet to reproduce this issue?</p>",964 "post_number": 2,965 "post_type": 1,966 "posts_count": 6,967 "updated_at": "2021-01-20T02:57:03.895Z",968 "reply_count": 1,969 "reply_to_post_number": null,970 "quote_count": 0,971 "incoming_link_count": 5,972 "reads": 15,973 "readers_count": 14,974 "score": 33.0,975 "yours": false,976 "topic_id": 109239,977 "topic_slug": "typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out",978 "display_username": "",979 "primary_group_name": null,980 "flair_name": null,981 "flair_url": null,982 "flair_bg_color": null,983 "flair_color": null,984 "flair_group_id": null,985 "badges_granted": [],986 "version": 1,987 "can_edit": false,988 "can_delete": false,989 "can_recover": false,990 "can_see_hidden_post": false,991 "can_wiki": false,992 "read": true,993 "user_title": "",994 "bookmarked": false,995 "actions_summary": [],996 "moderator": true,997 "admin": true,998 "staff": true,999 "user_id": 3534,1000 "hidden": false,1001 "trust_level": 2,1002 "deleted_at": null,1003 "user_deleted": false,1004 "edit_reason": null,1005 "can_view_edit_history": true,1006 "wiki": false,1007 "post_url": "/t/typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out/109239/2",1008 "can_accept_answer": false,1009 "can_unaccept_answer": false,1010 "accepted_answer": false,1011 "topic_accepted_answer": null1012 },1013 {1014 "id": 258181,1015 "name": "",1016 "username": "danielmanu93",1017 "avatar_template": "/letter_avatar_proxy/v4/letter/d/a88e4f/{size}.png",1018 "created_at": "2021-01-20T03:26:18.703Z",1019 "cooked": "<p><a class=\"mention\" href=\"/u/ptrblck\">@ptrblck</a>, the results for the print statements are shown in the image below. The tensor is the edge_index tuple with size “none”, “idx” prints “1” and edge_index[idx] prints a “none”.<br>\nWith the posting of executable code to reproduce the issue, that will be a lot of code files to post because I’m running the main program which import a lot of different python files to execute including this message passing code. Probably I can post the full message passing code so that you can have a look.<br>\n<img src=\"https://discuss.pytorch.org/uploads/default/original/3X/6/c/6c0ba9cd2c1a39d25ef603a7e0bbeb6f6e189bc1.jpeg\" alt=\"3\" data-base62-sha1=\"fpOyqw58fuDGjILB1dHZZD8crT3\" width=\"422\" height=\"57\"></p>",1020 "post_number": 3,1021 "post_type": 1,1022 "posts_count": 6,1023 "updated_at": "2021-01-20T03:26:18.703Z",1024 "reply_count": 1,1025 "reply_to_post_number": 2,1026 "quote_count": 0,1027 "incoming_link_count": 2,1028 "reads": 15,1029 "readers_count": 14,1030 "score": 18.0,1031 "yours": false,1032 "topic_id": 109239,1033 "topic_slug": "typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out",1034 "display_username": "",1035 "primary_group_name": null,1036 "flair_name": null,1037 "flair_url": null,1038 "flair_bg_color": null,1039 "flair_color": null,1040 "flair_group_id": null,1041 "badges_granted": [],1042 "version": 1,1043 "can_edit": false,1044 "can_delete": false,1045 "can_recover": false,1046 "can_see_hidden_post": false,1047 "can_wiki": false,1048 "read": true,1049 "user_title": null,1050 "reply_to_user": {1051 "id": 3534,1052 "username": "ptrblck",1053 "name": "",1054 "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png"1055 },1056 "bookmarked": false,1057 "actions_summary": [],1058 "moderator": false,1059 "admin": false,1060 "staff": false,1061 "user_id": 40263,1062 "hidden": false,1063 "trust_level": 1,1064 "deleted_at": null,1065 "user_deleted": false,1066 "edit_reason": null,1067 "can_view_edit_history": true,1068 "wiki": false,1069 "post_url": "/t/typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out/109239/3",1070 "can_accept_answer": false,1071 "can_unaccept_answer": false,1072 "accepted_answer": false,1073 "topic_accepted_answer": null1074 },1075 {1076 "id": 258182,1077 "name": "",1078 "username": "danielmanu93",1079 "avatar_template": "/letter_avatar_proxy/v4/letter/d/a88e4f/{size}.png",1080 "created_at": "2021-01-20T03:38:55.043Z",1081 "cooked": "<p>Here is the full message passing code:</p>\n<p>import inspect<br>\nimport torch<br>\nfrom torch_geometric.utils import scatter_</p>\n<p>class MessagePassing(torch.nn.Module):<br>\ndef <strong>init</strong>(self, aggr=‘add’, flow=‘source_to_target’):<br>\nsuper(MessagePassing, self).<strong>init</strong>()</p>\n<pre><code> self.aggr = aggr\n assert self.aggr in ['add', 'mean', 'max']\n\n self.flow = flow\n assert self.flow in ['source_to_target', 'target_to_source']\n\n self.message_args = inspect.getargspec(self.message)[0][1:]\n self.update_args = inspect.getargspec(self.update)[0][2:]\n\ndef propagate(self, edge_index, size=None, **kwargs):\n r\"\"\"The initial call to start propagating messages.\n\n Args:\n edge_index (Tensor): The indices of a general (sparse) assignment\n matrix with shape :obj:`[N, M]` (can be directed or\n undirected).\n size (list or tuple, optional): The size :obj:`[N, M]` of the\n assignment matrix. If set to :obj:`None`, the size is tried to\n get automatically inferrred. (default: :obj:`None`)\n **kwargs: Any additional data which is needed to construct messages\n and to update node embeddings.\n \"\"\"\n\n size = [None, None] if size is None else list(size)\n assert len(size) == 2\n\n kwargs['edge_index'] = edge_index\n i, j = (0, 1) if self.flow == 'target_to_source' else (1, 0)\n ij = {\"_i\": i, \"_j\": j}\n \n message_args = []\n for arg in self.message_args:\n if arg[-2:] in ij.keys():\n tmp = kwargs[arg[:-2]]\n if tmp is None:\n message_args.append(tmp)\n else:\n idx = ij[arg[-2:]]\n if isinstance(tmp, tuple):\n assert len(tmp) == 2\n if size[1 - idx] is None:\n size[1 - idx] = tmp[1 - idx].size(0)\n tmp = tmp[idx]\n\n if size[idx] is None:\n size[idx] = tmp.size(0)\n #print(edge_index)\n #print(edge_index[idx])\n #print(idx)\n tmp = torch.index_select(tmp, 0, edge_index[idx])\n message_args.append(tmp)\n else:\n message_args.append(kwargs[arg])\n\n size[0] = size[1] if size[0] is None else size[0]\n size[1] = size[0] if size[1] is None else size[1]\n\n kwargs['size'] = size\n update_args = [kwargs[arg] for arg in self.update_args]\n\n out = self.message(*message_args)\n if self.aggr in [\"add\", \"mean\", \"max\"]:\n out = scatter_(self.aggr, out, edge_index[i], dim_size=size[i])\n else:\n pass\n out = self.update(out, *update_args)\n\n return out\n\ndef message(self, x_j): # pragma: no cover\n return x_j\n\ndef update(self, aggr_out): # pragma: no cover\n return aggr_out</code></pre>",1082 "post_number": 4,1083 "post_type": 1,1084 "posts_count": 6,1085 "updated_at": "2021-01-23T23:25:56.721Z",1086 "reply_count": 1,1087 "reply_to_post_number": 3,1088 "quote_count": 0,1089 "incoming_link_count": 17,1090 "reads": 13,1091 "readers_count": 12,1092 "score": 92.6,1093 "yours": false,1094 "topic_id": 109239,1095 "topic_slug": "typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out",1096 "display_username": "",1097 "primary_group_name": null,1098 "flair_name": null,1099 "flair_url": null,1100 "flair_bg_color": null,1101 "flair_color": null,1102 "flair_group_id": null,1103 "badges_granted": [],1104 "version": 3,1105 "can_edit": false,1106 "can_delete": false,1107 "can_recover": false,1108 "can_see_hidden_post": false,1109 "can_wiki": false,1110 "read": true,1111 "user_title": null,1112 "reply_to_user": {1113 "id": 40263,1114 "username": "danielmanu93",1115 "name": "",1116 "avatar_template": "/letter_avatar_proxy/v4/letter/d/a88e4f/{size}.png"1117 },1118 "bookmarked": false,1119 "actions_summary": [],1120 "moderator": false,1121 "admin": false,1122 "staff": false,1123 "user_id": 40263,1124 "hidden": false,1125 "trust_level": 1,1126 "deleted_at": null,1127 "user_deleted": false,1128 "edit_reason": null,1129 "can_view_edit_history": true,1130 "wiki": false,1131 "post_url": "/t/typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out/109239/4",1132 "can_accept_answer": false,1133 "can_unaccept_answer": false,1134 "accepted_answer": false,1135 "topic_accepted_answer": null1136 },1137 {1138 "id": 258209,1139 "name": "",1140 "username": "ptrblck",1141 "avatar_template": "/user_avatar/discuss.pytorch.org/ptrblck/{size}/1823_2.png",1142 "created_at": "2021-01-20T06:58:39.605Z",1143 "cooked": "<p>Based on the posted outputs it seems <code>edge_index</code> is a <code>tuple</code> containing a tensor and <code>None</code>.<br>\nIf <code>idx</code> is set to <code>1</code>, you would index the <code>tuple</code> and get the <code>None</code> value as the return value.<br>\nI’m not sure what the <code>None</code> represents, but in case you want to index the stored tensor, you would have to use <code>edge_index[0][idx]</code>.</p>",1144 "post_number": 5,1145 "post_type": 1,1146 "posts_count": 6,1147 "updated_at": "2021-01-20T06:58:39.605Z",1148 "reply_count": 1,1149 "reply_to_post_number": 4,1150 "quote_count": 0,1151 "incoming_link_count": 6,1152 "reads": 10,1153 "readers_count": 9,1154 "score": 37.0,1155 "yours": false,1156 "topic_id": 109239,1157 "topic_slug": "typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out",1158 "display_username": "",1159 "primary_group_name": null,1160 "flair_name": null,1161 "flair_url": null,1162 "flair_bg_color": null,1163 "flair_color": null,1164 "flair_group_id": null,1165 "badges_granted": [],1166 "version": 1,1167 "can_edit": false,1168 "can_delete": false,1169 "can_recover": false,1170 "can_see_hidden_post": false,1171 "can_wiki": false,1172 "read": true,1173 "user_title": "",1174 "reply_to_user": {1175 "id": 40263,1176 "username": "danielmanu93",1177 "name": "",1178 "avatar_template": "/letter_avatar_proxy/v4/letter/d/a88e4f/{size}.png"1179 },1180 "bookmarked": false,1181 "actions_summary": [],1182 "moderator": true,1183 "admin": true,1184 "staff": true,1185 "user_id": 3534,1186 "hidden": false,1187 "trust_level": 2,1188 "deleted_at": null,1189 "user_deleted": false,1190 "edit_reason": null,1191 "can_view_edit_history": true,1192 "wiki": false,1193 "post_url": "/t/typeerror-index-select-received-an-invalid-combination-of-arguments-got-tensor-int-nonetype-but-expected-one-of-tensor-input-name-dim-tensor-index-tensor-out/109239/5",1194 "can_accept_answer": false,1195 "can_unaccept_answer": false,1196 "accepted_answer": false,1197 "topic_accepted_answer": null1198 },1199 {1200 "id": 258216,