Great work! Was wondering if you deal with transferring the python environment remotely. Usually a large part of the difficulty is dealing with dependencies.
We make sure the remote containers have CUDA/Pytorch/Numpy/Matplotlib set up if you're using a GPU-based machine. It's actually far easier for me to run ML-based code through Moonglow now than on my Macbook - it's really nice to start with a clean environment every time, instead of having to deal with dependency hell.
We don't yet transfer the python environment on the self-serve options, though for customers on AWS we'll help them create and maintain images with the packages they need.
I do have some ideas for making it easy to transfer environments over - it would probably involve letting people specify a requirements.txt and some apt dependencies and then automatically creating/deploying containers around that. Your idea of actually just detecting what's installed locally is pretty neat too, though.
bblcla|1 year ago
We don't yet transfer the python environment on the self-serve options, though for customers on AWS we'll help them create and maintain images with the packages they need.
I do have some ideas for making it easy to transfer environments over - it would probably involve letting people specify a requirements.txt and some apt dependencies and then automatically creating/deploying containers around that. Your idea of actually just detecting what's installed locally is pretty neat too, though.