Creating a conda Environment for Pytorch and Cuda

Happy Tuesday, Everyone. Trolol for the thumbnail.

Over the last week have been playing with some autoencoders and trying to build a model to fit the CosMx SMI data. However, getting started was a little frustrating because installing pytorch to use cuda on my machine was a little touch and go depending on order packages were installed. Here I thought to show the results of my troubleshooting so others wouldn't have to go through that process themselves and can start working with deep learning faster.

I don't have anything fancy installed on the main system (outside the conda environment) aside from the latest Nvidia drivers so this should be applicable to others in a similar situation. If you'd like to see videos of some deep learning in the future let me know - there are tons out there but perhaps we can apply it to some biological data in a fun new way.

GitHub repository for this showing the codes as well as a YML file for easy replication:
https://github.com/ACSoupir/cuda_conda/tree/main

Codes provided by Pytorch (whose order was adjusted to make installation on the system function properly without errors):
https://pytorch.org/get-started/locally/

Please consider contributing to my Patreon where I may do merch, gather ideas for future content, and have further discussions:
https://www.patreon.com/AlexSoupir

Тэги:

#deep_learning #reproducibility

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