## Urgent Upgrade Notes

### (No, really, you MUST read this before you upgrade)

#### Cluster Lifecycle

- Container images tar files for `amd64` will now contain the architecture in the RepoTags manifest.json section.
  If you are using docker manifests there are not visible changes. ([#80266](https://github.com/kubernetes/kubernetes/pull/80266), [@javier-b-perez](https://github.com/javier-b-perez))

<p>
An <i>integer</i>, <i>floating-point</i>, or <i>complex</i> type
represents the set of integer, floating-point, or complex values, respectively.
They are collectively called <i>numeric types</i>.
The predeclared architecture-independent numeric types are:
</p>

<pre class="grammar">
uint8       the set of all unsigned  8-bit integers (0 to 255)
uint16      the set of all unsigned 16-bit integers (0 to 65535)

"crypto/internal/impl" ) // This file contains code for using the 'compute intermediate // message digest' (KIMD) and 'compute last message digest' (KLMD) // instructions to compute SHA-3 and SHAKE hashes on IBM Z. See // [z/Architecture Principles of Operation, Fourteen Edition]. // // [z/Architecture Principles of Operation, Fourteen Edition]: https://www.ibm.com/docs/en/module_1678991624569/pdf/SA22-7832-13.pdf var useSHA3 = cpu.S390XHasSHA3 func init() { // CP Assist for Cryptographic Functions (CPACF) impl.Register("sha3",...

///

/// tip

🚥 👆 💭, "📊", "🎓", &amp; "🍏" 📛 🎰 🏫 <abbr title="Technically, Deep Learning model architectures">🏷</abbr>.

///

### 📣 *➡ 🔢*

⤴️ ✍ *➡ 🔢* ⏮️ 🆎 ✍ ⚙️ 🔢 🎓 👆 ✍ (`ModelName`):

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### ✅ 🩺

      <match value="DICM" type="string" offset="128"/>
    </magic>
  </mime-type>

  <mime-type type="application/dita+xml">
    <sub-class-of type="application/xml"/>
    <_comment>Darwin Information Typing Architecture</_comment>
  </mime-type>

  <mime-type type="application/dita+xml;format=map">
    <sub-class-of type="application/dita+xml"/>
    <_comment>DITA Map</_comment>
    <root-XML localName="map"/>

///

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

///

/// tip | Astuce

Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning.

///

### Déclarer un paramètre de chemin

///

/// tip | 豆知識

"AlexNet"、"ResNet"そして"LeNet"は機械学習<abbr title="Technically, Deep Learning model architectures">モデル</abbr>の名前です。

///

### *パスパラメータ*の宣言

次に、作成したenumクラスである`ModelName`を使用した型アノテーションをもつ*パスパラメータ*を作成します:

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### ドキュメントの確認

	"fmt"
	"internal/godebug"
	"io/fs"
	"maps"
	"math"
	"path"
	"reflect"
	"strconv"
	"strings"
	"time"
)

// BUG: Use of the Uid and Gid fields in Header could overflow on 32-bit
// architectures. If a large value is encountered when decoding, the result
// stored in Header will be the truncated version.

var tarinsecurepath = godebug.New("tarinsecurepath")

var (

    *   PV Recycle now works in environments that use architectures other than x86. ([#53958](https://github.com/kubernetes/kubernetes/pull/53958),[ @dixudx](https://github.com/dixudx))