Err:     "key with given key ID already exits",
	}

	// ErrKeyNotFound is an error returned by the KMS when trying to
	// use a key that does not exist.
	ErrKeyNotFound = Error{
		Code:    http.StatusNotFound,
		APICode: "kms:KeyNotFound",
		Err:     "key with given key ID does not exist",
	}

	// ErrDecrypt is an error returned by the KMS when the decryption
	// of a ciphertext failed.
	ErrDecrypt = Error{

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

* Из загруженного файла можно получить метаданные.
* Он реализует <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> `async` интерфейс.

# Is development environment here? (used for various purpose, you should set false if unknown)
development.here = false

# The title of environment (e.g. local or integration or production)
environment.title = Production

# Does it enable the Framework internal debug? (true only when emergency)
framework.debug = false

# one day: 86400000, three days: 259200000, five days: 432000000, one week: 604800000, one year: 31556926000

Sie können das unter <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a> sehen:

<img src="/img/tutorial/behind-a-proxy/image01.png">

Wenn wir jedoch unter der „offiziellen“ URL, über den Proxy mit Port `9999`, unter `/api/v1/docs`, auf die Dokumentationsoberfläche zugreifen, funktioniert es ordnungsgemäß! 🎉

输入 <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs 查看 API 文档：</a>

<img src="/img/tutorial/behind-a-proxy/image01.png">

但输入**官方**链接 `/api/v1/docs`，并使用端口 `9999` 访问 API 文档，就能正常运行了！🎉

输入 <a href="http://127.0.0.1:9999/api/v1/docs" class="external-link" target="_blank">http://127.0.0.1:9999/api/v1/docs 查看文档：</a>

<img src="/img/tutorial/behind-a-proxy/image02.png">

✋️ FastAPI 🐕‍🦺 ⚙️ <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> 🎏 🌌:

```Python hl_lines="1  7-12  19-20"
{!../../docs_src/dataclasses/tutorial001.py!}
```

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package gradlebuild.docs.dsl.docbook;

import gradlebuild.docs.dsl.docbook.model.DslElementDoc;
import org.w3c.dom.Document;
import org.w3c.dom.Element;

public class ElementWarningsRenderer {

    * In requests and responses will be represented as a `float` of total seconds.
    * Pydantic also allows representing it as a "ISO 8601 time diff encoding", <a href="https://docs.pydantic.dev/latest/concepts/serialization/#custom-serializers" class="external-link" target="_blank">see the docs for more info</a>.
* `frozenset`:
    * In requests and responses, treated the same as a `set`:

 */

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;