{* ../../docs_src/path_params/tutorial005_py310.py hl[18,21,23] *}

İstemcinizde şöyle bir JSON response alırsınız:

```JSON
{
  "model_name": "alexnet",
  "message": "Deep Learning FTW!"
}
```

## Path İçeren Path Parametreleri { #path-parameters-containing-paths }

Diyelim ki `/files/{file_path}` path'ine sahip bir *path operation*'ınız var.

* `foo` as an `int`
* `bar` as a `str`
* `baz` as a `list`

* the Tutorial - User guide
* the Advanced User Guide
* the SQLModel docs
* the API docs
* the automatic docs

* Data Science
* Deep Learning
* Machine Learning
* Dependency Injection
* HTTP Basic authentication
* HTTP Digest
* ISO format
* the JSON Schema standard
* the JSON schema
* the schema definition
* Password Flow

{* ../../docs_src/path_params/tutorial005_py310.py hl[18,21,23] *}

На стороні клієнта ви отримаєте відповідь у форматі JSON, наприклад:

```JSON
{
  "model_name": "alexnet",
  "message": "Deep Learning FTW!"
}
```

## Параметри шляху, що містять шляхи { #path-parameters-containing-paths }

Припустімо, у вас є *операція шляху* зі шляхом `/files/{file_path}`.

* L'apprentissage profond (ou **Deep Learning**) : est un sous-domaine du **Machine Learning**, donc les mêmes raisons s'appliquent. Avec la différence qu'il n'y a pas une unique feuille de calcul de nombres à multiplier, mais une énorme quantité d'entre elles, et dans de nombreux cas,...

* **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Piensa en una enorme hoja de cálculo con números y multiplicando todos juntos al mismo tiempo.

* **Maschinelles Lernen**: Normalerweise sind viele „Matrix“- und „Vektor“-Multiplikationen erforderlich. Stellen Sie sich eine riesige Tabelle mit Zahlen vor, in der Sie alle Zahlen gleichzeitig multiplizieren.

* 여러분
* 여러분의

* 예:
* 등

* `foo`로서의 `int`
* `bar`로서의 `str`
* `baz`로서의 `list`

* 튜토리얼 - 사용자 가이드
* 고급 사용자 가이드
* SQLModel 문서
* API 문서
* 자동 문서

* Data Science
* Deep Learning
* Machine Learning
* Dependency Injection
* HTTP Basic authentication
* HTTP Digest
* ISO format
* JSON Schema 표준
* JSON schema
* schema definition
* Password Flow
* Mobile

        -  If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.
        -  As a workaround, you could import the same private symbol keras `keras.src`, but keep in mind the `src` namespace is not stable and those APIs may change or be removed in the future.

### Major Features and Improvements

        assertFalse(deepDir.exists(), "Deep directory should not exist initially");

        deepDir.mkdirs();
        deepDir.close();
        Thread.sleep(200);

        CIFSContext checkContext = createFreshContext();
        SmbFile checkDeepDir = new SmbFile(baseUrl + "shared/level1_" + timestamp + "/level2/level3/", checkContext);
        assertTrue(checkDeepDir.exists(), "Deep directory should exist after creation");

- Client-go: informer stores now keep track the resourceVersion they are synced to (via add/update/delete events, or replace calls, or bookmark events), and provide a `LastStoreSyncResourceVersion` method to obtain this resource version. This method can return `""` if the store has not...