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Anurag1734/cuda-error-resolution-analysis

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1[2  {3    "post_stream": {4      "posts": [5        {6          "id": 120513,7          "name": "Anuj Chopra",8          "username": "Anuj_Chopra",9          "avatar_template": "/user_avatar/discuss.pytorch.org/anuj_chopra/{size}/9425_2.png",10          "created_at": "2019-07-02T05:24:15.685Z",11          "cooked": "<p>I want to create a simple gru which counts the number of ones in a sequence of 0s and 1s. Example<br>\ninput = 100110, output = 3<br>\ninput = 101, output = 2<br>\ninput = 10001110101, output = 6</p>\n<p>This is the way I have made my model.</p>\n<pre><code class=\"lang-auto\">class Counter(NN.Module):\n    def __init__(self, input_size,hidden_size, output_size):\n        super(Counter, self).__init__()\n        self.embed = NN.Embedding(input_size,hidden_size,)\n        self.hidden_size = hidden_size\n        self.output_size = output_size\n        self.gru = NN.GRU(hidden_size,hidden_size, batch_first = True,)\n        self.linear = NN.Linear(hidden_size, output_size)\n        \n    def forward(self,inputs, hidden = 0):\n        embedded = self.embed(inputs)\n        gru_out, gru_hid = self.gru(embedded)\n        final_out = self.linear(gru_out[:,-1])\n        return final_out\n\n</code></pre>\n<p>Now I make an object of this class with input size = 2 (0 or 1 which goes in embedding), hidden size = 5, and output size = 1 (total count of 1s in the number).<br>\nThe losses and optimizer are:</p>\n<pre><code class=\"lang-auto\">cc = Counter(2,5,1)\ncriterion = NN.MSELoss()\noptimizer = optim.SGD(cc.parameters(),lr = 0.01)\n</code></pre>\n<p>I am making my inputs and outputs through this function:</p>\n<pre><code class=\"lang-auto\">def get_number(digits = 10):\n    ones = np.random.choice(digits)\n    l = [1 if i &lt; ones else 0 for i in range(digits)]\n    l = np.random.permutation(l)\n    return l, ones\n</code></pre>\n<p>Now I am simply iterating multiple times to train. I also used scheduler and decaying learning rate. But I am not getting any good results. All I get is some value (close to average value of ones).</p>\n<pre><code class=\"lang-auto\">digits = 10\nfor r in range(iterations):\n    cc.zero_grad()\n    inputs = []\n    labels = []\n    for b in range(batch_size):\n        p,q = get_number(digits)\n        inputs.append(p)\n        labels.append(q *1.0)\n    outputs = cc.forward(torch.tensor(inputs))\n    loss = criterion(outputs, torch.tensor(labels))\n    temp_loss.append(loss.data.numpy())\n    loss.backward()\n    optimizer.step()\n</code></pre>\n<p>So here, since digits = 10, therefore I will get a model which predicts some value close to 5 everytime. <img src=\"https://discuss.pytorch.org/images/emoji/apple/expressionless.png?v=9\" title=\":expressionless:\" class=\"emoji\" alt=\":expressionless:\"><br>\nI guess it has something to do with gru, hidden layer because that is something which is still unclear to me. Please help.</p>",12          "post_number": 1,13          "post_type": 1,14          "posts_count": 5,15          "updated_at": "2019-07-04T06:19:19.828Z",16          "reply_count": 0,17          "reply_to_post_number": null,18          "quote_count": 0,19          "incoming_link_count": 82,20          "reads": 13,21          "readers_count": 12,22          "score": 412.6,23          "yours": false,24          "topic_id": 49433,25          "topic_slug": "gru-for-creating-a-simple-ones-counter",26          "display_username": "Anuj Chopra",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": 3,35          "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": 15900,48          "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/gru-for-creating-a-simple-ones-counter/49433/1",56          "can_accept_answer": false,57          "can_unaccept_answer": false,58          "accepted_answer": false,59          "topic_accepted_answer": null,60          "can_vote": false61        },62        {63          "id": 120519,64          "name": "Anuj Chopra",65          "username": "Anuj_Chopra",66          "avatar_template": "/user_avatar/discuss.pytorch.org/anuj_chopra/{size}/9425_2.png",67          "created_at": "2019-07-02T05:56:47.005Z",68          "cooked": "<p>I tried using L1loss, but getting similar results.</p>",69          "post_number": 2,70          "post_type": 1,71          "posts_count": 5,72          "updated_at": "2019-07-02T05:56:47.005Z",73          "reply_count": 1,74          "reply_to_post_number": null,75          "quote_count": 0,76          "incoming_link_count": 1,77          "reads": 14,78          "readers_count": 13,79          "score": 12.8,80          "yours": false,81          "topic_id": 49433,82          "topic_slug": "gru-for-creating-a-simple-ones-counter",83          "display_username": "Anuj Chopra",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": null,99          "bookmarked": false,100          "actions_summary": [],101          "moderator": false,102          "admin": false,103          "staff": false,104          "user_id": 15900,105          "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/gru-for-creating-a-simple-ones-counter/49433/2",113          "can_accept_answer": false,114          "can_unaccept_answer": false,115          "accepted_answer": false,116          "topic_accepted_answer": null117        },118        {119          "id": 121618,120          "name": "Chris",121          "username": "vdw",122          "avatar_template": "/user_avatar/discuss.pytorch.org/vdw/{size}/10074_2.png",123          "created_at": "2019-07-07T00:15:32.418Z",124          "cooked": "<p>OK, I have to ask: Why would you ever try to train an RNN to count the number of 1’s in a binary string? I actually don’t think this is a suitable task for a neural network. For once, your output is not bounded.</p>\n<p>Apart from that, why do you have an embedding layer? Your inputs are already numeric values. Embeddings are mainly needed to map words to meaningful vector representations for NLP tasks.</p>",125          "post_number": 3,126          "post_type": 1,127          "posts_count": 5,128          "updated_at": "2019-07-07T00:15:32.418Z",129          "reply_count": 1,130          "reply_to_post_number": 2,131          "quote_count": 0,132          "incoming_link_count": 0,133          "reads": 12,134          "readers_count": 11,135          "score": 7.4,136          "yours": false,137          "topic_id": 49433,138          "topic_slug": "gru-for-creating-a-simple-ones-counter",139          "display_username": "Chris",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": 1,148          "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": 15900,157            "username": "Anuj_Chopra",158            "name": "Anuj Chopra",159            "avatar_template": "/user_avatar/discuss.pytorch.org/anuj_chopra/{size}/9425_2.png"160          },161          "bookmarked": false,162          "actions_summary": [],163          "moderator": false,164          "admin": false,165          "staff": false,166          "user_id": 1438,167          "hidden": false,168          "trust_level": 2,169          "deleted_at": null,170          "user_deleted": false,171          "edit_reason": null,172          "can_view_edit_history": true,173          "wiki": false,174          "post_url": "/t/gru-for-creating-a-simple-ones-counter/49433/3",175          "can_accept_answer": false,176          "can_unaccept_answer": false,177          "accepted_answer": false,178          "topic_accepted_answer": null179        },180        {181          "id": 121761,182          "name": "Anuj Chopra",183          "username": "Anuj_Chopra",184          "avatar_template": "/user_avatar/discuss.pytorch.org/anuj_chopra/{size}/9425_2.png",185          "created_at": "2019-07-08T05:58:18.003Z",186          "cooked": "<p>Why would you ever try to train an RNN to count the number of 1’s in a binary string?<br>\nI am doing this for my own learning. In theory rnn should be able to do this task. It is not impossible to do this.<br>\nApart from that, why do you have an embedding layer?<br>\nI have an embedding layer (which I think will not deteriorate the performance) because once I am successful in this task, I plan to make a “A” counter or any other alphabet/character counter. I know we can make counters just by regex, but rnn should also be able to do this. I was able to make a rnn which counted “1” if I sent the string one-by-one (hidden state has the count till now, input is the next value 1/0 and output is either count+1 or count) . But that is an easy task for rnn, just take decision either to add or not to add. I wanted to make a rnn which carries the count in its hidden state.<br>\nIn case you have any suggestion/solution, it would be of great help.</p>",187          "post_number": 4,188          "post_type": 1,189          "posts_count": 5,190          "updated_at": "2019-07-08T06:27:19.663Z",191          "reply_count": 0,192          "reply_to_post_number": 3,193          "quote_count": 0,194          "incoming_link_count": 3,195          "reads": 11,196          "readers_count": 10,197          "score": 17.2,198          "yours": false,199          "topic_id": 49433,200          "topic_slug": "gru-for-creating-a-simple-ones-counter",201          "display_username": "Anuj Chopra",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          "badges_granted": [],209          "version": 2,210          "can_edit": false,211          "can_delete": false,212          "can_recover": false,213          "can_see_hidden_post": false,214          "can_wiki": false,215          "read": true,216          "user_title": null,217          "reply_to_user": {218            "id": 1438,219            "username": "vdw",220            "name": "Chris",221            "avatar_template": "/user_avatar/discuss.pytorch.org/vdw/{size}/10074_2.png"222          },223          "bookmarked": false,224          "actions_summary": [],225          "moderator": false,226          "admin": false,227          "staff": false,228          "user_id": 15900,229          "hidden": false,230          "trust_level": 2,231          "deleted_at": null,232          "user_deleted": false,233          "edit_reason": null,234          "can_view_edit_history": true,235          "wiki": false,236          "post_url": "/t/gru-for-creating-a-simple-ones-counter/49433/4",237          "can_accept_answer": false,238          "can_unaccept_answer": false,239          "accepted_answer": false,240          "topic_accepted_answer": null241        },242        {243          "id": 124906,244          "name": "Anuj Chopra",245          "username": "Anuj_Chopra",246          "avatar_template": "/user_avatar/discuss.pytorch.org/anuj_chopra/{size}/9425_2.png",247          "created_at": "2019-07-23T11:09:17.613Z",248          "cooked": "<p>I was able to do this perfectly. I was making very basic mistake in calculating loss. Instead of<br>\n<code>loss = criterion(outputs, torch.tensor(labels))</code><br>\nI needed to use<br>\n<code>loss = criterion(outputs[:,0], torch.tensor(labels))</code><br>\nand the model works perfectly. Infact GRU does it very well. Anyways thanks for trying to help me.</p>",249          "post_number": 5,250          "post_type": 1,251          "posts_count": 5,252          "updated_at": "2019-07-23T11:09:17.613Z",253          "reply_count": 0,254          "reply_to_post_number": null,255          "quote_count": 0,256          "incoming_link_count": 1,257          "reads": 6,258          "readers_count": 5,259          "score": 6.2,260          "yours": false,261          "topic_id": 49433,262          "topic_slug": "gru-for-creating-a-simple-ones-counter",263          "display_username": "Anuj Chopra",264          "primary_group_name": null,265          "flair_name": null,266          "flair_url": null,267          "flair_bg_color": null,268          "flair_color": null,269          "flair_group_id": null,270          "badges_granted": [],271          "version": 1,272          "can_edit": false,273          "can_delete": false,274          "can_recover": false,275          "can_see_hidden_post": false,276         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