Kubeadm: Automate certificate copy between control planes in HA setups

- Joining control plane nodes to a HA cluster can now be simplified by enabling the optional automatic copy of certificates from an existing control plane node.
- You can now use `kubeadm init --experimental-upload-certs` and `kubeadm join --experimental-control-plane --certificate-key`.

    *   Support for IPv6-only Kubernetes cluster deployments. **<span style="text-decoration:underline;">Note:</span>** This feature does not provide dual-stack support.
    *   Support for IPv6 Kubernetes control and data planes.
    *   Support for Kubernetes IPv6 cluster deployments using kubeadm.
    *   Support for the iptables kube-proxy backend using ip6tables.
    *   Relies on CNI 0.6.0 binaries for IPv6 pod networking.

")+"["+Dn[this.day()]+"] LT[-kor]"}function wn(e){return e%100==11||e%10!=1}function vn(e,a,t,s){var n=e+" ";switch(t){case"s":return a||s?"nokkrar sek\xfandur":"nokkrum sek\xfandum";case"ss":return wn(e)?n+(a||s?"sek\xfandur":"sek\xfandum"):n+"sek\xfanda";case"m":return a?"m\xedn\xfata":"m\xedn\xfatu";case"mm":return wn(e)?n+(a||s?"m\xedn\xfatur":"m\xedn\xfatum"):a?n+"m\xedn\xfata":n+"m\xedn\xfatu";case"hh":return wn(e)?n+(a||s?"klukkustundir":"klukkustundum"):n+"klukkustund";case"d":return a?"da...

CX, X7 PXOR X8, X8 PCMPEQL X9, X9 PSHUFD $0x00, X6, X6 PSHUFD $0x00, X7, X7 PCMPEQL X8, X6 PCMPEQL X8, X7 MOVOU X6, X15 PANDN X9, X15 MOVOU (SP), X9 MOVOU 16(SP), X10 MOVOU 32(SP), X11 MOVOU 48(SP), X12 MOVOU 64(SP), X13 MOVOU 80(SP), X14 PAND X15, X0 PAND X15, X1 PAND X15, X2 PAND X15, X3 PAND X15, X4 PAND X15, X5 PAND X6, X9 PAND X6, X10 PAND X6, X11 PAND X6, X12 PAND X6, X13 PAND X6, X14 PXOR X9, X0 PXOR X10, X1 PXOR X11, X2 PXOR X12, X3 PXOR X13, X4 PXOR X14, X5 // Similarly if zero == 0 PCMPEQL...

*   `tf.experimental.StructuredTensor`

    *   Introduced `tf.experimental.StructuredTensor`, which provides a flexible
        and Tensorflow-native way to encode structured data such as protocol
        buffers or pandas dataframes.

*   `tf.keras`:

    *   Added method `get_metrics_result()` to `tf.keras.models.Model`.
        *   Returns the current metrics values of the model as a dict.