For Monte Carlo simulations, Pyro and tensorflow_probability have also nice abstractions.
Yes, tested and used Jax for some prototyping but it felt like still has "two language problem". But Taichi looks quite interesting, will check out.
Of course, forgot to mention, it has to be lightweight, torch and tf are now huge platforms. Not sure, probably Julia-lang is much small.
If you are just programming using pre-existing libraries, and using those libraries the way the author intended them to be used, then for most cases Python is probably fine, but if you are doing something relatively novel that some big framework doesn't cover for you, that's where I think Julia really stands out and makes a big difference relative to Python.
I really recommend giving it a try.
Protip: "optimize=True" is equivalent to "optimize='greedy'", but you may prefer "optimize='optimal'" for big cases or use a list precalculated by einsum_path.
condensedcrab•1mo ago
Both don’t just work out of the box like Julia or MATLAB’s “parfor” loop, but seem to work well enough for non trivial for loop cases.
northlondoner•1mo ago
condensedcrab•1mo ago