Hi all, I’m currently have a tensor with side BxNxD (batch size x num sample each block x dimension)
Can anybody come across give me a help, please? I want to speed up the following computation:
K = Kernel() # similar with https://github.com/activatedgeek/svgd/blob/master/rbf.py
sum = 0
for i in range(B):
    sum += K(tensor[i], tensor[i]) 

It calculate kernel of a NxD tensor (which returns a NxN tensor) and then sum over the minibatch