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I'm still learning from deep learning papers and videos before dipping my toes in myself, is there a summary of why PyTorch vs TensorFlow? Does it matter for me
by AaronFriel 6y ago
I'm still learning from deep learning papers and videos before dipping my toes in myself, is there a summary of why PyTorch vs TensorFlow? Does it matter for me?
- minimaxir 6y agoNowadays, there isn't a huge practical difference in terms of performance/tooling aside from edge cases and deployment options. It mostly depends on your syntax preference. (although there are flame wars from both sides) I noted the TensorFlow usage because the original GPT-2 release was TensorFlow 1.X, which led to issues when TensorFlow 2.0 was released soon after. For model training, I strongly recommend using the higher-level Keras APIs for TensorFlow/pytorch-lightning API for PyTorch than the respective base tools.
- m0zg 6y agoThere is a huge difference in developer experience still. When TF fails it typically offers little to no clue as to what you can do to rectify the situation. PyTorch is a lot more helpful most of the time. PyTorch is worth choosing on this basis alone, unless you intend to deploy to mobile hardware, where TFLite is the only real viable option.
- fxtentacle 6y agoTF can compile to optimized C++. When you use PyTorch with TPU, it'll internally use the TF XLA backend. If you intend to deploy on mobile, TF is easy and PyTorch is pain. But TF has obscure bugs and error messages.
- deleted 6y ago[deleted]
- currymj 6y agojust use PyTorch, it’s generally going to be the nicest. TF2 is much nicer than TF1 but most of the changes were just to make it more like PyTorch.