* Allow having empty paths in *path operations* used with `include_router` and a `prefix`.
    * This allows having a router for `/cats` and all its *path operations*, while having one of them for `/cats`.
    * Now it doesn't have to be only `/cats/` (with a trailing slash).

*   `tf.data`:

    *   tf.data service now supports auto-sharding. Users specify the sharding
        policy with `tf.data.experimental.service.ShardingPolicy` enum. It can
        be one of `OFF` (equivalent to today's `"parallel_epochs"` mode),
        `DYNAMIC` (equivalent to today's `"distributed_epoch"` mode), or one of
        the static sharding policies: `FILE`, `DATA`, `FILE_OR_DATA`, or `HINT`

bernetes.io/docs/reference/scheduling/config) feature allows you to tune the algorithms and other settings of the kube-scheduler. You can easily enable or disable specific functionality (contained in plugins) in selected scheduling phases without having to rewrite the rest of the configuration. Furthermore, a single kube-scheduler instance can serve different configurations, called profiles. Pods can select the profile they want to be scheduled under via the `.spec.schedulerName` field.

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1FADC..1FADF  ; disallowed                             # NA   <reserved-1FADC>..<reserved-1FADF>
1FAE0..1FAE7  ; valid                  ;      ; NV8    # 14.0 MELTING FACE..BUBBLES
1FAE8         ; valid                  ;      ; NV8    # 15.0 SHAKING FACE
1FAE9..1FAEF  ; disallowed                             # NA   <reserved-1FAE9>..<reserved-1FAEF>
1FAF0..1FAF6  ; valid                  ;      ; NV8    # 14.0 HAND WITH INDEX FINGER AND THUMB CROSSED..HEART HANDS

func rr(m *Modulus) *Nat { rr := NewNat().ExpandFor(m) n := uint(len(rr.limbs)) 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...