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It's not that simple. Pytorch has its own computing model, calling it just APIs is really downplaying the phenomenal works behind the framework. Pytorch put Ten
by anvuong 3y ago
It's not that simple. Pytorch has its own computing model, calling it just APIs is really downplaying the phenomenal works behind the framework. Pytorch put Tensorflow to shame even though the latter had huge first mover advantage.
- godelski 3y agoFor sure it's not that simple, but the person I was responding to was at the stage of understanding that they were thinking PyTorch was better than CUDA. I'm trying to communicate to them, not someone with a more detailed understanding (I mean one of the top comments here thinks ML is "just matrix multiplies"...) Tensorflow had first mover advantage but they also had first mover disadvantage. TF isn't that easy to write nor to debug. PyTorch got to see everything that was wrong with TF and fix it. No doubt Meta has put in lots of amazing effort. It is an incredible piece of software. I'll also add that PyTorch does a lot of great stuff that people don't use or recognize. There are a lot of good distributional works out there for prob and stats people that give you cuda acceleration. Really a lot of numpy can be replaced with pytorch and its great. But be warned of FMA and other optimization differences.