mLen := uint(m.BitLen()) logR := _W * n // We start by computing R = 2^(_W * n) mod m. We can get pretty close, to // 2^⌊log₂m⌋, by setting the highest bit we can without having to reduce. rr.limbs[n-1] = 1 << ((mLen - 1) % _W) // Then we double until we reach 2^(_W * n). for i := mLen - 1; i < logR; i++ { rr.Add(rr, m) } // Next we need to get from R to 2^(_W * n) R mod m (aka from one to R in // the Montgomery domain, meaning we can use Montgomery multiplication now). // We could do that by doubling...

*  Added `keras.utils.TimedThread` utility to run a timed thread every x seconds. It can be used to run a threaded function alongside model training or any other snippet of code.