and `tf.data.Dataset.range`.
    *   Promote `tf.data.Options.experimental_deterministic` API to
        `tf.data.Options.deterministic` and deprecate the experimental endpoint.
    *   Move autotuning options
        from`tf.data.Options.experimental_optimization.autotune*` to a newly
        created `tf.data.Options.autotune.*` and remove support for
        `tf.data.Options.experimental_optimization.autotune_buffers`.

pkg crypto/ed25519, func VerifyWithOptions(PublicKey, []uint8, []uint8, *Options) error #31804
pkg crypto/ed25519, method (*Options) HashFunc() crypto.Hash #31804
pkg crypto/ed25519, type Options struct #31804
pkg crypto/ed25519, type Options struct, Context string #31804
pkg crypto/ed25519, type Options struct, Hash crypto.Hash #31804
pkg crypto/rsa, type OAEPOptions struct, MGFHash crypto.Hash #19974

y[2], c) t1[3], c = bits.Add64(x[3], y[3], c) t2 := make([]uint64, 4) t2[0], b = bits.Sub64(t1[0], p256P[0], 0) t2[1], b = bits.Sub64(t1[1], p256P[1], b) t2[2], b = bits.Sub64(t1[2], p256P[2], b) t2[3], b = bits.Sub64(t1[3], p256P[3], b) // Three options: // - a+b < p // then c is 0, b is 1, and t1 is correct // - p <= a+b < 2^256 // then c is 0, b is 0, and t2 is correct // - 2^256 <= a+b // then c is 1, b is 1, and t2 is correct t2Mask := (c ^ b) - 1 res[0] = (t1[0] & ^t2Mask) | (t2[0] & t2Mask)...