title stringlengths 15 126 | category stringclasses 3
values | posts list | answered bool 2
classes |
|---|---|---|---|
[resolved] Has anyone noticed significant slowdown after upgrading to v0.1.11? | null | [
{
"contents": "Yesterday I upgraded my pytorch to v0.1.11. I ran the same training script. I noticed that the time for each batch has increased from 0.8 seconds to 2.9 seconds. Nothing is changed except the pytorch. My old version is 0.1.9+67f9455. Now I am trying to upgrade to cudnn v6 to see whether it could ... | false |
How to demonstrate (or teach) learning theory using PyTorch | null | [
{
"contents": "Hi, There’s a lot of beautiful theory on function approximation, for example, is quite readable.",
"isAccepted": false,
"likes": 1,
"poster": "AjayTalati"
},
{
"contents": "I’d be interested in implementing them in PyTorch - I’ll be doing some DL theory teaching/demos over the... | false |
Mysterious nn.Parameter behavior | null | [
{
"contents": "<SCODE>import torch\nfrom torch import nn\n\nclass Model(nn.Module):\n def __init__(self, deg):\n\tsuper(Model, self).__init__()\n\tself.deg = deg + 1\n\n\tself.theta = nn.Parameter(torch.ones(self.deg), 1)\n\n def forward(self, xs):\n\tphi = torch.cat([xs**i for i in range(self.deg)], 1)\... | false |
RuntimeError: Assertion `THCTensor_(checkGPU)(state, 3, dst, src, indices)’ failed | null | [
{
"contents": "I have trained a simple sequence to sequence model and saved the model in file. Now when I loaded the model and trying to do the testing, I am getting the following error. I am getting error at the following line. embedded = self.embedding(input).view(1, 1, -1) I am guessing the problem is not in... | false |
Argmax with PyTorch | null | [
{
"contents": "How can I use argmax with PyTorch? Meta: How could I have answered my own question? I searched the PyTorch docs and the PyTorch repo for “argmax” but got no results. Does it make sense to use argmax with a GPU?",
"isAccepted": true,
"likes": 8,
"poster": "MatthewKleinsmith"
},
{
... | true |
Constructing a matrix variable from other variables | null | [
{
"contents": "I’m trying to construct a rotation matrix from the Euler angles. As simple as I feel this should be, I’m not sure what the best approach is in PyTorch. Is there a way to do this without spamming torch.cat? Essentially I just to want to stack some existing tensor variables into a matrix for conven... | false |
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