cuda-libraries-dev-12-8
cuda-nvml-dev-12-8
libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.8.0.87-1

* 따라서 이미지, 동영상, 큰 이진코드와 같은 대용량 파일들을 많은 메모리를 소모하지 않고 처리하기에 적합합니다.
* 업로드 된 파일의 메타데이터를 얻을 수 있습니다.
* <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a>  `async` 인터페이스를 갖고 있습니다.
* file-like object를 필요로하는 다른 라이브러리에 직접적으로 전달할 수 있는 파이썬 <a href="https://docs.python.org/3/library/tempfile.html#tempfile.SpooledTemporaryFile" class="external-link" target="_blank">`SpooledTemporaryFile`</a> 객체를 반환합니다.

 */

package gradlebuild.docs;

import org.gradle.api.Plugin;
import org.gradle.api.Project;
import org.gradle.api.artifacts.Configuration;
import org.gradle.api.file.ConfigurableFileTree;
import org.gradle.api.file.ProjectLayout;
import org.gradle.api.model.ObjectFactory;
import org.gradle.api.tasks.TaskContainer;
import org.gradle.api.tasks.TaskProvider;
import gradlebuild.docs.dsl.docbook.AssembleDslDocTask;

items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The Bar fighters", "price": 62, "tax": 20.2},
    "baz": {
        "name": "Baz",
        "description": "There goes my baz",
        "price": 50.2,
        "tax": 10.5,
    },
}


@app.get(
    "/items/{item_id}/name",
    response_model=Item,
    response_model_include=["name", "description"],
)

- `tuned`
- `curl`

### Install `tuned.conf` performance profile

#### Step 1 - download `tuned.conf` from the referenced link
```
wget https://raw.githubusercontent.com/minio/minio/master/docs/tuning/tuned.conf
```

#### Step 2 - install tuned.conf as supported performance profile on all nodes
```
sudo mkdir -p /usr/lib/tuned/minio/
sudo mv tuned.conf /usr/lib/tuned/minio
```

## URL-адреса документации { #docs-urls }

Вы можете изменить конфигурацию двух пользовательских интерфейсов документации, которые включены:

* **Swagger UI**: отображаемый по адресу `/docs`.
    * Вы можете задать его URL с помощью параметра `docs_url`.
    * Вы можете отключить это с помощью настройки `docs_url=None`.

**FastAPI** **extraerá** los datos de **cada campo** de los **form data** en el request y te dará el modelo de Pydantic que definiste.

## Revisa la Documentación { #check-the-docs }

Puedes verificarlo en la interfaz de documentación en `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

## Prohibir Campos de Formulario Extra { #forbid-extra-form-fields }

 * limitations under the License.
 */
package gradlebuild.docs.dsl.docbook

import gradlebuild.docs.dsl.docbook.model.BlockDoc
import gradlebuild.docs.dsl.docbook.model.ClassDoc
import gradlebuild.docs.dsl.docbook.model.ClassExtensionDoc
import gradlebuild.docs.dsl.docbook.model.ExtraAttributeDoc
import gradlebuild.docs.dsl.docbook.model.MethodDoc
import gradlebuild.docs.dsl.docbook.model.PropertyDoc
import gradlebuild.docs.XmlSpecification

cuda-libraries-dev-13-0
cuda-nvml-dev-13-0
libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-headers-cuda-13=9.12.0.46-1
libcudnn9-static-cuda-13=9.12.0.46-1
libcudnn9-dev-cuda-13=9.12.0.46-1

///

## Custom Headers { #custom-headers }

Keep in mind that custom proprietary headers can be added <a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers" class="external-link" target="_blank">using the `X-` prefix</a>.