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Would you be able to sketch what makes PyTorch better than TF? And maybe why Google are sticking with TF -- it's not like Google lack technical ability to do /
by Loq 7y ago
Would you be able to sketch what makes PyTorch better than TF? And maybe why Google are sticking with TF -- it's not like Google lack technical ability to do / copy what PyTorch does.
- m0zg 7y agoIt's basically imperative GPU accelerated NumPy with autograd and really nice libraries. You can be productive in it in a day (much less if you already know numpy), and if something goes wrong, it tells you what went wrong. It's also easily twice as fast as TF on GPU, trivial to use on multi-GPU setups, has an easy to use dataset interface, and allows you to run batches that are twice as large (which means faster training). Google certainly has _technical_ capacity to do what PyTorch does, but not the _organizational_ capacity to scrap TF and start over. So they're trying to half-ass it with TF 2.0. It still sucks though.
- chillee 7y agoThere's a discussion here of sorts: https://www.reddit.com/r/MachineLearning/comments/cvcbu6/d_why_is_pytorch_as_fast_as_and_sometimes_faster/ https://www.reddit.com/r/MachineLearning/comments/cvcbu6/d_w... Perhaps Google could copy PyTorch. But Tensorflow has a lot of overhead, and for both political/technical reasons, there's no easy path to go from Tensorflow to Pytorch. You could just as easily ask: Why is Google sticking with {Hangouts/(Allo,Duo)/Angular} instead of doing/copying {Zoom/WhatsApp/React}? It's not like Google lacks the technical ability.