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run-ai / genv

GPU environment and cluster management with LLM support
https://www.genv.dev
GNU Affero General Public License v3.0
447 stars 20 forks source link

Configure CUDA and other library versions #11

Closed djwessel closed 1 year ago

djwessel commented 1 year ago

Hey, first of all, really cool idea for a tool.

One of the most annoying aspects of sharing a workstation with others is managing different needs for library versions (cuDNN, CUDA Toolkit, etc.). While PyTorch handles this by wrapping the required libraries into the python module, TensorFlow still requires users to install the necessary library versions themselves.

Do you consider supporting the management of the different library/driver versions per environment through this tool?

jonathancosme commented 1 year ago

@djwessel you can actually use conda to manage this.

  1. create your conda environments with the appropriate packages and version
  2. activate your conda environment
  3. use genv commands within the activated conda environment

You can watch a live example of how this is done here (starting at 4:38): https://youtu.be/_WZR_aO73LU

djwessel commented 1 year ago

Thanks, so there is a separation of concerns between the different tools.