In the documentation it shows that by hybridizing you get nearly a 2x performance boost, so I was wondering how each compares to other iterative frameworks, particularly PyTorch. It seems to me that PyTorch’s iterative paradigm is similar to using NDArray, so then is using Symbol twice as fast as PyTorch?
Borealis AI did a comparison between Gluon and PyTorch recently which you might find useful: http://www.borealisai.com/2018/02/16/standardizing-a-machine-learning-framework-for-applied-research/
Thanks! That is a very interesting article. I really wish they had explored hybridization, although since they were using an RNN it’s understandable.