Does pytorch has potential for efficient inference of fully binirized (XNOR) conv nets?

I understand that using some hacks I could train xnor net, but what about efficient inference? Does pytorch support fair bitwise xnor-conv operations?


No bitwise convolutions are not supported.
But the ones in the paper have the input as floats and the weights as binary values?

Most element-wise bitwise operations are implemented for ByteTensors such as and, or, nor, xor… You can do dir(torch.ByteTensor()) to see what is there, most like __xor__.

This is not what I want

Can I do Conv2d with torch.ByteTensor or torch.CharTensor?


No only float convolutions are supported.