You might also find Halide[1] interesting then. It too is a computation graph that does a good job of separating core algorithm and optimizations. OpenCV's neu

You might also find Halide[1] interesting then. It too is a computation graph that does a good job of separating core algorithm and optimizations. OpenCV's neural networks module actually uses Halide as an optional backend. I found it to be a practical approach to run TF/Torch/Caffe/Darknet models on CPUs and OpenCL/AMD. There was an OpenCV proposal to port all algorithms to Halide API [1]. I think that's still the long term plan, and G-API is a kind of stopgap till then [2]. [1]: http://halide-lang.org/ http://halide-lang.org/ [2]: https://github.com/opencv/opencv/wiki/OE-23.-Module-GAPI https://github.com/opencv/opencv/wiki/OE-23.-Module-GAPI