Nvidia rtx a6000 gpu incompatible with pytorch

username: tjk
cooked: <p>Hello guys:<br>
I try to run a machine learning program with NVIDIA RTX A6000 graphical cards and Pytorch, but confronted with the following problem:<br>
Traceback (most recent call last):</p>
<p>File"D:\jktong\LCNIl-FIT-exp-size\250by250\Train_directions_complex_gpu_large_u7.3.py", line 223, in loss.backward()<br>
File “c: \Users \hplanaconda3\libisite-packages \torch\tensor.py " , line 245,in backward torch.autograd.backward(self, gradient,retain_graph,create_graph，inputs=inputs)<br>
File"c:\Users\hplanaconda3\liblsite-packages \torchlautogradl_init_.py",line 145,in backward variable._execution_engine.run_backward(</p>
<p>RuntimeError: cuDNN error: CUDNN_STATUS_NOT_INITIALIZED<br>
The program can be run smoothly on three NVIDIA RTX 2080Ti graphical cards, so it seems that our program has no problems.</p>
<p>The cuda version of our workstation is 11.1, cudnn version is 11.3 and pytorch version is 1.8.2.<br>
I have tried to search for the recommended version of pytorch with this graphical cards, but it seems this card is too new, could you please give us some suggestions to solve the problem (like recommend a suitable version of pytorch for this GPU)? Thank you!</p>

username: ptrblck
cooked: <p>I guess you might be using the PyTorch binaries with the CUDA 10.2 runtime, while you would need CUDA&gt;=11.0. Check the shipped CUDA version via <code>print(torch.version.cuda)</code> and make sure it’s 11.</p>
<aside class="quote no-group" data-username="tjk" data-post="1" data-topic="135450">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://discuss.pytorch.org/letter_avatar_proxy/v4/letter/t/dec6dc/48.png" class="avatar"> tjk:</div>
<blockquote>
<p>The cuda version of our workstation is 11.1, cudnn version is 11.3 and pytorch version is 1.8.2.</p>
</blockquote>
</aside>
<p>Your local CUDA toolkit won’t be used if you’ve installed the binaries, as they ship with their own CUDA runtime, cuDNN, NCCL etc., unless you are building from source or a custom CUDA extension (also cuDNN is currently at version 8, so you might have read the wrong version tag).</p>

username: tjk
cooked: <p>Hello, we uninstalled the CUDA 10.0 on our workstation before re-install CUDA 11.0, will the cases said by you occur in the computer?</p>

username: tjk
cooked: <p>We executed print(torch.version.cuda) and it outputs 11.1<img src="https://discuss.pytorch.org/uploads/default/original/3X/2/3/23d9194399be460bf2da62a049c0b3876f917e82.png" alt="截图" data-base62-sha1="577QhufeIOpkjbNBgTTjav0goiC" width="242" height="51"></p>

username: tjk
cooked: <p>if I try to print the loss object with spyder, it will print the following error:<br>
loss<br>
Traceback (most recent call last):</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\IPython\core\formatters.py”, line 702, in <strong>call</strong><br>
printer.pretty(obj)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\IPython\lib\pretty.py”, line 394, in pretty<br>
return _repr_pprint(obj, self, cycle)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\IPython\lib\pretty.py”, line 700, in _repr_pprint<br>
output = repr(obj)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\torch\tensor.py”, line 193, in <strong>repr</strong><br>
return torch._tensor_str._str(self)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\torch_tensor_str.py”, line 383, in _str<br>
return _str_intern(self)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\torch_tensor_str.py”, line 358, in _str_intern<br>
tensor_str = _tensor_str(self, indent)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\torch_tensor_str.py”, line 242, in _tensor_str<br>
formatter = _Formatter(get_summarized_data(self) if summarize else self)</p>
<p>File “C:\Users\hp\anaconda3\lib\site-packages\torch_tensor_str.py”, line 90, in <strong>init</strong><br>
nonzero_finite_vals = torch.masked_select(tensor_view, torch.isfinite(tensor_view) &amp; tensor_view.ne(0))</p>
<p>RuntimeError: CUDA error: an illegal memory access was encountered</p>