[argonaut]

You're making the language out to be more important than it really is.

The Python that you write when using these frameworks just the glue code / scripts. All you're doing is calling the framework's functions. Most of it gets thrown away (as researchers). The stuff that doesn't is self-contained and usually short. You're not writing 100k+ line codebases.

Lua may be faster for certain tasks (data processing), but the time it takes for does tasks is usually a rounding error in deep learning. Not to mention you can still code in C/C++ with pytorch.

If there is a monoculture in machine learning, it would be the deep learning monoculture.