Hi there, I’m not sure if this is the right place to ask, but I just installed cuda tools to run some GPU-based machine learning stuff on my computer, and I’m running into an issue importing torch.
I’m on Ubuntu 22.04 with python 3.10.12.
I installed torch via pip3 install torch torchvision torchaudio
If I run python3:
Python 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.version.cuda
'12.1'
When I run nvcc -V my output is:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Thu_Mar_28_02:18:24_PDT_2024
Cuda compilation tools, release 12.4, V12.4.131
Build cuda_12.4.r12.4/compiler.34097967_0
When I run nvidia-smi my output is:
NVIDIA-SMI 550.67 Driver Version: 550.67 CUDA Version: 12.4
I have an NVIDIA GeForce RTX 3050 Ti.
Based on Table 3 of CUDA Compatibility :: NVIDIA GPU Management and Deployment Documentation, CUDA 12.4 seems like the right version for my NVIDIA driver.
I’m able to run python3 -c 'import torch' with no output, which I assume is good news.
That being said, when I try to import torch into a jupyter notebook, I get the error:
ModuleNotFoundError: No module named 'torch._custom_ops'; 'torch' is not a package
I was able to find torch._custom_ops myself, so I know it exists, but I’m not sure why it isn’t working in Jupyter Notebook?
I found this: python - Loading a pretrained model from torch.hub in Sagemaker - Stack Overflow but that didn’t seem relevant given I’m not using Sagemaker and simply trying to get my local machine ready to tackle GPU training tasks.
I would appreciate any help, insight, or simply comments telling me a better place to be asking this question.
Thank you