Hi,
I’m afraid that on cpu, we have a single convolution implementation. Which is one based on matrix matrix multiplication. This is very good for small kernel but will create huge matrices if the kernel ia big. I don’t remember any plan to add more implementations.
If you’re using the gpu, by using torch.backends.cudnn.benchmark=True you should be able to get an algorithm that will be efficient for your use case.