Something like this
if v0 is a 1x K vector and conv is a a NxMxK you can rearrange conv into a (NxM)xK vector and perform matrix multiuplication
    def multiply(v0,conv):
        N,M,K = conv.size()
        conv = conv.view(N*M,K)
        return torch.mm(conv,v0.unsqueeze(0)).view(N,M,K)