returns q. The points may overlap. func (q *P256Point) Add(r1, r2 *P256Point) *P256Point { var sum, double P256Point r1IsInfinity := r1.isInfinity() r2IsInfinity := r2.isInfinity() pointsEqual := p256PointAddAsm(&sum, r1, r2) p256PointDoubleAsm(&double, r1) p256MovCond(&sum, &double, &sum, pointsEqual) p256MovCond(&sum, r1, &sum, r2IsInfinity) p256MovCond(&sum, r2, &sum, r1IsInfinity) return q.Set(&sum) } // Double sets q = p + p, and returns q. The points may overlap. func (q *P256Point) Double(p...

        Keras training loops like `fit`/`evaluate`, the unreduced vector loss is
        passed to the optimizer but the reported loss will be a scalar value.
    *   `SUM`: Scalar sum of weighted losses. 4. `SUM_OVER_BATCH_SIZE`: Scalar
        `SUM` divided by number of elements in losses. This reduction type is
        not supported when used with `tf.distribute.Strategy` outside of
        built-in training loops like `tf.keras` `compile`/`fit`.

pkg hash/maphash, method (*Hash) Reset()
pkg hash/maphash, method (*Hash) Seed() Seed
pkg hash/maphash, method (*Hash) SetSeed(Seed)
pkg hash/maphash, method (*Hash) Size() int
pkg hash/maphash, method (*Hash) Sum([]uint8) []uint8
pkg hash/maphash, method (*Hash) Sum64() uint64
pkg hash/maphash, method (*Hash) Write([]uint8) (int, error)
pkg hash/maphash, method (*Hash) WriteByte(uint8) error