These 1-bit-per-coefficient neural nets need pretty good floating point implementation to train them. From what I remember, they are trained with rounding - bas

These 1-bit-per-coefficient neural nets need pretty good floating point implementation to train them. From what I remember, they are trained with rounding - basically, a floating point weight gets rounded to -1, 0 or 1 and computed floating point gradient is added to a floating point weight. Inference is cheap, training is not.