---

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.
* **Computer vision**: an image is composed of millions of pixels, each pixel has 3 values / colors, processing that normally requires computing something on those pixels, all at the same time.

在这些情况下，你可以使用 **官方 Docker 镜像**，其中包含 **Gunicorn** 作为运行多个 **Uvicorn 工作进程** 的进程管理器，以及一些默认设置来根据当前情况调整工作进程数量 自动CPU核心。 我将在下面的 [Gunicorn - Uvicorn 官方 Docker 镜像](#official-docker-image-with-gunicorn-uvicorn) 中告诉你更多相关信息。

下面一些什么时候这种做法有意义的示例：


#### 一个简单的应用程序

如果你的应用程序**足够简单**，你不需要（至少现在不需要）过多地微调进程数量，并且你可以使用自动默认值，那么你可能需要容器中的进程管理器 （使用官方 Docker 镜像），并且你在**单个服务器**而不是集群上运行它。

* <a href="https://fastapi.tiangolo.com/js/logic.js" class="external-link" target="_blank">Link to a script</a>
* <a href="https://fastapi.tiangolo.com/img/foo.jpg" class="external-link" target="_blank">Link to an image</a>

The link text should get translated, the link address should point to the translation:

* <a href="https://fastapi.tiangolo.com/" class="external-link" target="_blank">FastAPI link</a>

////

    to fix this.
-   Once the internal tests pass, we go ahead and merge the code internally as
    well as externally on GitHub.

In a graphical form, the entire lifetime of a PR looks like

![image](https://github.com/tensorflow/tensorflow/assets/52792999/3eea4ca5-daa0-4570-b0b5-2a2b03a724a3)

### Contributor License Agreements

     Material is a musical work, performance, or sound recording,
     Adapted Material is always produced where the Licensed Material is
     synched in timed relation with a moving image.

  b. Adapter's License means the license You apply to Your Copyright
     and Similar Rights in Your contributions to Adapted Material in
     accordance with the terms and conditions of this Public License.

		echo Removing docker $container
		docker rm -f $container >/dev/null 2>&1
		docker wait $container
	done
}

function cleanup_and_prune() {
	cleanup
	docker system prune --volumes --force
	docker image prune --all --force
}

function verify_resiliency() {
	docs/resiliency/resiliency-verify-script.sh
	RESULT=$(grep "script passed" <resiliency-verify.log)
	if [ "$RESULT" != "script passed" ]; then

* **Cloud-Dienste**, welche das für Sie erledigen
    * Der Cloud-Dienst wird wahrscheinlich **die Replikation für Sie übernehmen**. Er würde Sie möglicherweise **einen auszuführenden Prozess** oder ein **zu verwendendes Container-Image** definieren lassen, in jedem Fall wäre es höchstwahrscheinlich **ein einzelner Uvicorn-Prozess**, und der Cloud-Dienst wäre auch verantwortlich für die Replikation.

/// tip | Tipp

* **Cloud services** that handle this for you
    * The cloud service will probably **handle replication for you**. It would possibly let you define **a process to run**, or a **container image** to use, in any case, it would most probably be **a single Uvicorn process**, and the cloud service would be in charge of replicating it.

/// tip

	// execute the HTTP request to create bucket.
	response, err := s.client.Do(request)
	c.Assert(err, nil)
	c.Assert(response.StatusCode, http.StatusOK)

	// Uploading a new object with Content-Type "image/png".
	// content for the object to be uploaded.
	buffer1 := bytes.NewReader([]byte("hello world"))
	objectName := "test-object.png"
	// constructing HTTP request for object upload.

Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes.

Par exemple :

* Traitements d'**audio** et d'**images**.
* La **vision par ordinateur** : une image est composée de millions de pixels, chaque pixel ayant 3 valeurs / couleurs, les traiter tous va nécessiter d'effectuer des traitements sur chaque pixel, et de préférence tous en même temps.