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Anurag1734/cuda-error-resolution-analysis

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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 438356,7          "name": "Satya Prakash Dash",8          "username": "sprakashdash",9          "avatar_template": "/user_avatar/discuss.pytorch.org/sprakashdash/{size}/48780_2.png",10          "created_at": "2024-04-04T21:40:35.180Z",11          "cooked": "<p>I have an index tensor like we send input to a bert model after tokenization, so the shape is <code>[batch_size, seq_len]</code> and I have to return a tensor with <code>0</code>’s and <code>1</code>’s (<code>1</code>’s where the indices are matched) of shape <code>[batch_size, seq_len, vocab_size]</code>.</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 3,15          "updated_at": "2024-04-04T21:40:35.180Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 33,20          "reads": 6,21          "readers_count": 5,22          "score": 166.2,23          "yours": false,24          "topic_id": 200269,25          "topic_slug": "create-binary-tensor-from-index-tensor",26          "display_username": "Satya Prakash Dash",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": 45903,48          "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/create-binary-tensor-from-index-tensor/200269/1",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": 438389,64          "name": "Satya Prakash Dash",65          "username": "sprakashdash",66          "avatar_template": "/user_avatar/discuss.pytorch.org/sprakashdash/{size}/48780_2.png",67          "created_at": "2024-04-05T10:52:37.615Z",68          "cooked": "<p>The closest solution I could find is to use <a href=\"https://pytorch.org/functorch/stable/generated/functorch.vmap.html\" rel=\"noopener nofollow ugc\">vmap</a>.<br>\nI defined a function to take an index and dimension and output a <code>torch.zeros</code> of the given dim (which is a 1-dimensional for my case) and add 1 to a specific index.</p>\n<pre><code class=\"lang-auto\">def idx2tensor(val, dim):         # apply this across second dimension\n            empty_tensor = torch.zeros(dim)\n            empty_tensor[val] = 1\n</code></pre>\n<p>Now I am applying vmap for an input tensor of shape <code>[batch_size, seq_length]</code> and expect to get <code>[batch_size, seq_length, dim]</code>.<br>\n<code>batched_idx2ten = torch.vmap(idx2tensor, in_dims=(0, None))</code> following <a href=\"https://pytorch.org/functorch/stable/generated/functorch.vmap.html#:~:text=If%20there%20are%20multiple%20inputs%20each%20of%20which%20is%20batched%20along%20different%20dimensions%2C%20in_dims%20must%20be%20a%20tuple%20with%20the%20batch%20dimension%20for%20each%20input%20as\" rel=\"noopener nofollow ugc\">this example in docs</a>.<br>\nApply the <code>batched_idx2ten</code> to a random input and a fixed dim:</p>\n<pre><code class=\"lang-auto\">x = 10 * torch.rand(4, 10) - 1\nx = torch.tensor(x, dtype=torch.int64)\nbatched_idx2ten(x, 15)\n</code></pre>\n<p>I am now stuck with the following error:</p>\n<pre><code class=\"lang-auto\">---------------------------------------------------------------------------\nRuntimeError                              Traceback (most recent call last)\n&lt;ipython-input-26-80c94fc2eaa3&gt; in &lt;cell line: 2&gt;()\n      1 x = 10 * torch.rand(4, 10) - 1\n----&gt; 2 batched_idx2ten(x, 15)\n\n4 frames\n/usr/local/lib/python3.10/dist-packages/torch/_functorch/apis.py in wrapped(*args, **kwargs)\n    186     # @functools.wraps(func)\n    187     def wrapped(*args, **kwargs):\n--&gt; 188         return vmap_impl(func, in_dims, out_dims, randomness, chunk_size, *args, **kwargs)\n    189 \n    190     return wrapped\n\n/usr/local/lib/python3.10/dist-packages/torch/_functorch/vmap.py in vmap_impl(func, in_dims, out_dims, randomness, chunk_size, *args, **kwargs)\n    276 \n    277     # If chunk_size is not specified.\n--&gt; 278     return _flat_vmap(\n    279         func, batch_size, flat_in_dims, flat_args, args_spec, out_dims, randomness, **kwargs\n    280     )\n\n/usr/local/lib/python3.10/dist-packages/torch/_functorch/vmap.py in fn(*args, **kwargs)\n     42     def fn(*args, **kwargs):\n     43         with torch.autograd.graph.disable_saved_tensors_hooks(message):\n---&gt; 44             return f(*args, **kwargs)\n     45     return fn\n     46 \n\n/usr/local/lib/python3.10/dist-packages/torch/_functorch/vmap.py in _flat_vmap(func, batch_size, flat_in_dims, flat_args, args_spec, out_dims, randomness, **kwargs)\n    389     try:\n    390         batched_inputs = _create_batched_inputs(flat_in_dims, flat_args, vmap_level, args_spec)\n--&gt; 391         batched_outputs = func(*batched_inputs, **kwargs)\n    392         return _unwrap_batched(batched_outputs, out_dims, vmap_level, batch_size, func)\n    393     finally:\n\n&lt;ipython-input-25-c7783e629350&gt; in idx2tensor(val, dim)\n      1 def idx2tensor(val, dim):         # apply this across second dimension\n      2     empty_tensor = torch.zeros(dim)\n----&gt; 3     empty_tensor[val] = 1\n      4 \n      5 batched_idx2ten = torch.vmap(idx2tensor, in_dims=(0, None))\n\nRuntimeError: vmap: index_put_(self, *extra_args) is not possible because there exists a Tensor `other`\nin extra_args that has more elements than `self`. This happened due to `other` being vmapped over but\n`self` not being vmapped over in a vmap. Please try to use out-of-place operators instead of index_put_. \nIf said operator is being called inside the PyTorch framework, please file a bug report instead.\n</code></pre>",69          "post_number": 2,70          "post_type": 1,71          "posts_count": 3,72          "updated_at": "2024-04-05T11:19:09.922Z",73          "reply_count": 1,74          "reply_to_post_number": null,75          "quote_count": 0,76          "incoming_link_count": 0,77          "reads": 6,78          "readers_count": 5,79          "score": 6.2,80          "yours": false,81          "topic_id": 200269,82          "topic_slug": "create-binary-tensor-from-index-tensor",83          "display_username": "Satya Prakash Dash",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": 2,92          "can_edit": false,93          "can_delete": false,94          "can_recover": false,95          "can_see_hidden_post": false,96          "can_wiki": false,97          "link_counts": [98            {99              "url": "https://pytorch.org/functorch/stable/generated/functorch.vmap.html",100              "internal": false,101              "reflection": false,102              "title": "functorch.vmap — functorch nightly documentation",103              "clicks": 0104            },105            {106              "url": "https://pytorch.org/functorch/stable/generated/functorch.vmap.html#:~:text=If%20there%20are%20multiple%20inputs%20each%20of%20which%20is%20batched%20along%20different%20dimensions%2C%20in_dims%20must%20be%20a%20tuple%20with%20the%20batch%20dimension%20for%20each%20input%20as",107              "internal": false,108              "reflection": false,109              "title": "functorch.vmap — functorch nightly documentation",110              "clicks": 0111            }112          ],113          "read": true,114          "user_title": null,115          "bookmarked": false,116          "actions_summary": [],117          "moderator": false,118          "admin": false,119          "staff": false,120          "user_id": 45903,121          "hidden": false,122          "trust_level": 2,123          "deleted_at": null,124          "user_deleted": false,125          "edit_reason": null,126          "can_view_edit_history": true,127          "wiki": false,128          "post_url": "/t/create-binary-tensor-from-index-tensor/200269/2",129          "can_accept_answer": false,130          "can_unaccept_answer": false,131          "accepted_answer": false,132          "topic_accepted_answer": true133        },134        {135          "id": 438417,136          "name": "K. Frank",137          "username": "KFrank",138          "avatar_template": "/letter_avatar_proxy/v4/letter/k/ecb155/{size}.png",139          "created_at": "2024-04-05T15:32:22.780Z",140          "cooked": "<p>Hi Satya!</p>\n<aside class=\"quote no-group\" data-username=\"sprakashdash\" data-post=\"2\" data-topic=\"200269\" 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/sprakashdash/48/48780_2.png\" class=\"avatar\"> sprakashdash:</div>\n<blockquote>\n<pre><code class=\"lang-auto\">def idx2tensor(val, dim):         # apply this across second dimension\n            empty_tensor = torch.zeros(dim)\n            empty_tensor[val] = 1\n</code></pre>\n</blockquote>\n</aside>\n<p>I believe that you are looking for <code>torch.nn.functional.one_hot()</code>:</p>\n<pre><code class=\"lang-plaintext\">&gt;&gt;&gt; import torch\n&gt;&gt;&gt; torch.__version__\n'2.2.2'\n&gt;&gt;&gt; _ = torch.manual_seed (2024)\n&gt;&gt;&gt; x = 10 * torch.rand(4, 10) - 1\n&gt;&gt;&gt; x = torch.tensor(x, dtype=torch.int64)\n&lt;stdin&gt;:1: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n&gt;&gt;&gt; x\ntensor([[4, 7, 8, 0, 0, 2, 1, 5, 3, 6],\n        [0, 4, 0, 6, 8, 3, 2, 8, 6, 5],\n        [7, 8, 5, 5, 1, 4, 1, 6, 0, 0],\n        [1, 0, 8, 5, 5, 3, 4, 0, 2, 4]])\n&gt;&gt;&gt; result = torch.nn.functional.one_hot (x, 15)\n&gt;&gt;&gt; result.shape\ntorch.Size([4, 10, 15])\n&gt;&gt;&gt; result[0]\ntensor([[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],\n        [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n        [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]])\n</code></pre>\n<p>Best.</p>\n<p>K. Frank</p>",141          "post_number": 3,142          "post_type": 1,143          "posts_count": 3,144          "updated_at": "2024-04-05T15:32:22.780Z",145          "reply_count": 0,146          "reply_to_post_number": 2,147          "quote_count": 1,148          "incoming_link_count": 6,149          "reads": 4,150          "readers_count": 3,151          "score": 45.8,152          "yours": false,153          "topic_id": 200269,154          "topic_slug": "create-binary-tensor-from-index-tensor",155          "display_username": "K. 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Frank",520      "excerpt": "Hi Satya! \n\nI believe that you are looking for torch.nn.functional.one_hot(): \n&gt;&gt;&gt; import torch\n&gt;&gt;&gt; torch.__version__\n&#39;2.2.2&#39;\n&gt;&gt;&gt; _ = torch.manual_seed (2024)\n&gt;&gt;&gt; x = 10 * torch.rand(4, 10) - 1\n&gt;&gt;&gt; x = torch.tensor(x, dtype=torch.int64)\n&lt;stdin&gt;:1: UserWarning: To copy construct from a tensor, it is &hellip;"521    },522    "can_vote": false,523    "vote_count": 0,524    "user_voted": false,525    "discourse_zendesk_plugin_zendesk_id": null,526    "discourse_zendesk_plugin_zendesk_url": "https://your-url.zendesk.com/agent/tickets/",527    "details": {528      "can_edit": false,529      "notification_level": 1,530      "participants": [531        {532          "id": 45903,533          "username": "sprakashdash",534          "name": "Satya Prakash Dash",535          "avatar_template": "/user_avatar/discuss.pytorch.org/sprakashdash/{size}/48780_2.png",536          "post_count": 2,537          "primary_group_name": null,538          "flair_name": null,539          "flair_url": null,540          "flair_color": null,541          "flair_bg_color": null,542          "flair_group_id": null,543          "trust_level": 2544        },545        {546          "id": 18088,547          "username": "KFrank",548          "name": "K. 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Frank",570        "avatar_template": "/letter_avatar_proxy/v4/letter/k/ecb155/{size}.png"571      }572    },573    "bookmarks": []574  },575  {576    "post_stream": {577      "posts": [578        {579          "id": 438052,580          "name": "ViktorPavlovA",581          "username": "ViktorPavlovA",582          "avatar_template": "/user_avatar/discuss.pytorch.org/viktorpavlova/{size}/68931_2.png",583          "created_at": "2024-04-02T18:55:48.931Z",584          "cooked": "<p>Hello.</p>\n<p>I have jetson xavier nx. I have already install version of torch-2.1.0a0+41361538.nv23.06-cp38-cp38-linux_aarch64.whl with using this <a href=\"https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048\" rel=\"noopener nofollow ugc\">guide</a> .  But i don’t found correct version of torchvision. it must be 0.15.1  but what’s the name of the branch ? I guess i try wrong branch…</p>\n<p>Thank you!</p>",585          "post_number": 1,586          "post_type": 1,587          "posts_count": 4,588          "updated_at": "2024-04-02T19:39:20.974Z",589          "reply_count": 0,590          "reply_to_post_number": null,591          "quote_count": 0,592          "incoming_link_count": 500,593          "reads": 4,594          "readers_count": 3,595          "score": 2490.8,596          "yours": false,597          "topic_id": 200103,598          "topic_slug": "trouble-with-installing-torchvision-on-jetson-xavier-nx",599          "display_username": "ViktorPavlovA",600          "primary_group_name": null,601          "flair_name": null,602          "flair_url": null,603          "flair_bg_color": null,604          "flair_color": null,605          "flair_group_id": null,606          "badges_granted": [],607          "version": 2,608          "can_edit": false,609          "can_delete": false,610          "can_recover": false,611          "can_see_hidden_post": false,612          "can_wiki": false,613          "link_counts": [614            {615              "url": "https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048",616              "internal": false,617              "reflection": false,618              "title": "PyTorch for Jetson - 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Thank you! But it’s not correct branch.</p>",721          "post_number": 3,722          "post_type": 1,723          "posts_count": 4,724          "updated_at": "2024-04-05T06:24:25.213Z",725          "reply_count": 1,726          "reply_to_post_number": null,727          "quote_count": 0,728          "incoming_link_count": 4,729          "reads": 4,730          "readers_count": 3,731          "score": 25.8,732          "yours": false,733          "topic_id": 200103,734          "topic_slug": "trouble-with-installing-torchvision-on-jetson-xavier-nx",735          "display_username": "ViktorPavlovA",736          "primary_group_name": null,737          "flair_name": null,738          "flair_url": null,739          "flair_bg_color": null,740          "flair_color": null,741          "flair_group_id": null,742          "badges_granted": [],743          "version": 1,744          "can_edit": false,745          "can_delete": false,746          "can_recover": false,747          "can_see_hidden_post": 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