Usage

This repository contains some useful scripts and configurations for setting up a new working environment, particularly for deep learning research.

Scripts

The scripts directory contains the following scripts:

Script	Description
switch-cuda.sh	Switch between different CUDA versions.
setup_git.sh	Setup git configurations.
setup_conda.sh	Install and setup conda configurations.
test_python_env.sh	Test python environment.

Frequently used commands

• To install PyTorch with CUDA support (refer to PyTorch)

conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia

• Check status of nvidia driver (e.g., when nvidia-smi is not working).

dkms status
sudo dpkg --configure -a

References

Some useful configuration and scripts to configure a new working environment.

CUDA compatibility

Actually we need not worry about the preinstalled cuda versions. According to this reply

the pip wheels and conda binaries ship with their own CUDA runtime as mentioned before. The system-wide installed CUDA toolkit will be used if you are building PyTorch from source or a custom CUDA extenstion.

To switch between cuda versions, refer to switch-cuda