### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.
name | architectures
---- | -------------

!!! 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*

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

```Python hl_lines="16"

!!! 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

Créez ensuite un *paramètre de chemin* avec une annotation de type désignant l'énumération créée précédemment (`ModelName`) :

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

### 📣 *➡ 🔢*

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

```Python hl_lines="16"
{!../../../docs_src/path_params/tutorial005.py!}
```

### ✅ 🩺

	}
	c := p.peek()
	if c == ':' || c == ',' || c == '+' {
		// 2nd register; syntax (R1+R2) etc. No two architectures agree.
		// Check the architectures match the syntax.
		switch p.next().ScanToken {
		case ',':
			if !p.arch.InFamily(sys.ARM, sys.ARM64) {
				p.errorf("(register,register) not supported on this architecture")
				return
			}
		case '+':
			if p.arch.Family != sys.PPC64 {

!!! 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:

```Python hl_lines="16"
{!../../../docs_src/path_params/tutorial005.py!}
```

### ドキュメントの確認

import (
	"errors"
	"fmt"
	"internal/godebug"
	"io/fs"
	"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 (

# The build-linux target is responsible for building binaries used within containers.
# This target should be expanded upon as we add more Linux architectures: i.e. build-arm64.
# Then a new build target can be created such as build-container-bin that builds these
# various platform images.
.PHONY: build-linux
build-linux: depend