It all started when I wanted to work with Fastai library which at some point led me to install Pytorch first. Anyway, I always get False when calling torch.cuda.is_available() and None when calling torch.version.cuda
This is on Ubuntu 18.04
nvidia-smi outputs
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 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 GeForce ... On | 00000000:65:00.0 Off | N/A |
| 41% 22C P8 16W / 260W | 18MiB / 11264MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2129 G /usr/lib/xorg/Xorg 9MiB |
| 0 N/A N/A 2393 G /usr/bin/gnome-shell 6MiB |
+-----------------------------------------------------------------------------+
By running collect_env
Collecting environment information...
PyTorch version: 1.7.1
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A
OS: Ubuntu 18.04.5 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.27
Python version: 3.9.12 (main, Apr 5 2022, 06:56:58) [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-4.15.0-175-generic-x86_64-with-glibc2.27
Is CUDA available: False
CUDA runtime version: 9.1.85
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 2080 Ti
Nvidia driver version: 510.47.03
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: torch.backends.xnnpack.enabled
Versions of relevant libraries:
[pip3] numpy==1.19.2
[pip3] torch==1.7.1
[pip3] torchaudio==0.7.0a0+a853dff
[pip3] torchvision==0.8.0a0
[conda] _pytorch_select 0.1 cpu_0
[conda] blas 1.0 mkl
[conda] cudatoolkit 9.0 h13b8566_0
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] libmklml 2019.0.5 h06a4308_0
[conda] mkl 2020.2 256
[conda] mkl-service 2.3.0 py39he8ac12f_0
[conda] mkl_fft 1.3.0 py39h54f3939_0
[conda] mkl_random 1.0.2 py39h63df603_0
[conda] numpy 1.19.2 py39h89c1606_0
[conda] numpy-base 1.19.2 py39h2ae0177_0
[conda] pytorch 1.7.1 cpu_py39h6a09485_0
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torchaudio 0.7.2 py39 fastchan
[conda] torchvision 0.8.2 cpu_py39ha229d99_0
and nvcc --version outputs
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
I tried many versions and many installations, since I got CUDA 9.01 I chose the versions appears here but also did not work.
However, when I tried to look for CUDA location it was in the directory /usr/local/cuda-10.1/
Do you think that the CUDA installation is messed up? This is a server on my university that I do research on. I think some students messed up things. I need some advice on what is best to do to fix CUDA and run Pytorch successfully.