Sm_86 is not compatible with current pytorch version

Mrunal_Sompura: <pre><code class="lang-auto">NVIDIA RTX A4000 with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
</code></pre>
<p>Here is output of python -m torch.utils.collect_env</p>
<pre><code class="lang-auto">Collecting environment information...
PyTorch version: 1.11.0
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.4 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.9.12 (main, Apr  5 2022, 06:56:58)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: 11.3.109
GPU models and configuration: GPU 0: NVIDIA RTX A4000
Nvidia driver version: 512.59
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.4.0
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.21.5
[pip3] torch==1.11.0
[pip3] torchaudio==0.11.0
[pip3] torchsummary==1.5.1
[pip3] torchvision==0.12.0
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               11.3.1               h2bc3f7f_2
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640
[conda] mkl-service               2.4.0            py39h7f8727e_0
[conda] mkl_fft                   1.3.1            py39hd3c417c_0
[conda] mkl_random                1.2.2            py39h51133e4_0
[conda] numpy                     1.21.5           py39he7a7128_2
[conda] numpy-base                1.21.5           py39hf524024_2
[conda] pytorch                   1.11.0          py3.9_cuda11.3_cudnn8.2.0_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torchaudio                0.11.0               py39_cu113    pytorch
[conda] torchsummary              1.5.1                    pypi_0    pypi
[conda] torchvision               0.12.0               py39_cu113    pytorch
</code></pre>
<p>Here is output of nvidia-smi</p>
<pre><code class="lang-auto">+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.68.01    Driver Version: 512.59       CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA RTX A4000    On   | 00000000:65:00.0  On |                    0 |
| 41%   29C    P8    13W / 140W |    326MiB / 15352MiB |      2%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
</code></pre>
<p>I have tried uninstallation/installation so many times. cant figure out why is this happening?</p>

ptrblck: <p>Based on the error message you’ve installed a PyTorch release with the CUDA10.2 runtime, which doesn’t match the posted environment. Uninstall all PyTorch installations and reinstall the PyTorch release with CUDA11 or create a new environment and reinstall it there.</p>

Eylul_Mood: <p>I have the same issue, did you solve the problem?</p>

ptrblck: <p>You might be running into the same issue of using the older CUDA 10.2 runtime.<br>
Uninstall all other PyTorch binaries and install the PyTorch binary with CUDA11.3 or 11.6.</p>

Eylul_Mood: <p>Ok thank you Ill try</p>

Arielle_Z: <p>I tried to install torch==1.9.0 for CUDA = 11.6, but still getting the same error. Should I reinstall CUDA with version = 11.3?</p>

ptrblck: <p><code>torch==1.9.0</code> should not have supported CUDA 11.6 at all, so I’m unsure where you are getting the binary from. Use the latest stable release (<code>1.12.1</code>) with a supported CUDA runtime (e.g. 11.6).</p>

Arielle_Z: <p>Thanks, yea then I have to install the corresponding version of torchvision right?</p>

ptrblck: <p>Yes, I would keep all packages compatible to each other by installing the versions corresponding to the same releases.</p>