[D] Any way to speed up simple mathematical functions without implementing cuda kernels for pytorch?

I am working on a pytorch project and I have a custom computation that I am so far unable to express as a combination pre-defined pytorch functions (because it's essentially some loops around conv2d calls where I juggle some indices in a 5-d tensor). So currently I use python-loops with some smart padding but that's not the fastest. The only way to speed this up would be, i think, to implement custom cuda kernels. While the computation is not that …

cuda machinelearning pytorch