This is amazing! It might be a personal feeling, but my opinion is that Facebook is SO much better than Google at delivering open source libraries that people want, and support them in the best way.<p>React vs Angular, Pytorch vs Tensorflow. These are just two examples among many where the Facebook framework arrives a bit later on the market but is then supported awesomely and improved continuously while the Google framework arrives earlier but then becomes a hot mess of non retro compatible upgrades and deprecations...<p>My “loyalty” to Facebook open source libraries just keep growing.
Yes yes yes! I've been anticipating this for so long.<p>However I'm a bit skeptical about doing quantization after training, in my experience you have to do quantization-aware training for there not be a large performance decrease. I guess it works though otherwise they wouldn't have released it?
Does anyone else have to maintain backend PyTorch based services? Is it just me or is it a complete mess?<p>Members of my team have spent literal months tracking down memory leaks, the performance of these services are always sub-par to Tensorflow based ones and the less said about the atrocious memory/cpu usage the better.<p>What's the advantage of using PyTorch when you have things like Tensorflow Serving ready to productionize any model with ease?
This is a common trend for being second in market, when we see Pytorch and TensorFlow 2.0, TF 2.0 was created to compete directly with Pytorch pythonic implementation (Keras based, Eager execution). Facebook at least on Pytorch has been delivering a quality product. Although for us running production pipelines TF is still ahead in many areas (GPU, TPU implementation, TensorRT, TFX and other pipeline tools) I can see Pytorch catching up on the next couple of years which by my prediction many companies will be running serious and advanced workflows and we may be able to see a winner there.
Might be a stupid question, but what's the advantage of using PyTorch Mobile, compared to converting to ONNX-> TF -> TF lite
(or something similar)
As a side point, looking at maven and the org.pytorch gave me a cold shudder remembering my java days.<p>How does CocoaPods compare to Maven, NuGet, or NPM?