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It's not like any performance significant component of the ML stack is actually implemented in Python. Everything is and has always been cuda, c or c++ under th
by geysersam 3y ago
It's not like any performance significant component of the ML stack is actually implemented in Python.
Everything is and has always been cuda, c or c++ under the hood.
Python is just the extremely effective glue binding it all together.
- brucethemoose2 3y agoSometimes implementations will spend a little too much time in Python interpretation, but yeah, its largely lower level code. The problem with PyTorch specifically is that (without Triton compilation) pretty much all projects run in eager mode. That's fine for experimentation and demonstrations in papers, but its crazy that its used so much for production without any compilation. It would be like using debug C binaries for production, and they only work with any kind of sane performance on a single CPU maker.