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Anyone have a ballpark estimate of Tensorflow models in production vs PyTorch? Is it something like 90/10?
by hn2017 7y ago
Anyone have a ballpark estimate of Tensorflow models in production vs PyTorch? Is it something like 90/10?
- Jwarder 7y agoLooks like 3:1 ish. https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/ https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-...
- dahart 7y agoWhich estimate are you looking at? The main thing I see is: “PyTorch and TensorFlow for Production Although PyTorch is now dominant in research, a quick glance at industry shows that TensorFlow is still the dominant framework. For example, based on data from 2018 to 2019, TensorFlow had 1541 new job listings vs. 1437 job listings for PyTorch on public job boards, 3230 new TensorFlow Medium articles vs. 1200 PyTorch, 13.7k new GitHub stars for TensorFlow vs 7.2k for PyTorch, etc.” That suggests 1:1 for jobs, 2:1 for github stars and 3:1 for articles on Medium. Really hard to say if any of those reflect uses in production in any meaningful way, but if so, I’d suggest that the jobs and/or github stars might be more useful than articles on Medium.
- Jwarder 7y agoThe jobs numbers suggests where the trend is going. The github and article counts seem more useful to indicate the current state. When looking at those numbers I'd rather pick the more conservative number.
- mark_l_watson 7y agoI have used TensorFlow almost exclusively for my deep learning work in the last five years and using TensorFlow is much more common, largely I think, because Andrew Ng’s excellent five part course used it. On the other hand Jerry Howards’s wonderful free classes use mostly PyTorch so maybe my argument does not hold. For research and for use in published papers, PyTorch is much more widely used.