import org.gradle.api.provider.Provider
import org.gradle.api.tasks.Nested
import org.gradle.api.tasks.TaskContainer
import org.gradle.util.GradleVersion
import java.util.Optional

/**
 * A project extension which describes a module of a Gradle distribution.
 */
abstract class GradleModuleExtension(val tasks: TaskContainer, val objects: ObjectFactory) {

    companion object {
        const val NAME: String = "gradleModule"
    }

   *     must be positive
   */
  public static Scale scale(int scale) {
    return new Scale(scale);
  }

  /**
   * Describes the point in a fluent API chain where only the scale (i.e. the q in q-quantiles) has
   * been specified.
   *
   * @since 20.0
   */
  public static final class Scale {

    private final int scale;

        // Test constructor with long strings
        String type = "VeryLongTokenTypeNameForTestingPurposes";
        String message =
                "This is a very long error message that describes in detail why the access token is invalid and what went wrong during validation";
        InvalidAccessTokenException exception = new InvalidAccessTokenException(type, message);

        assertEquals(type, exception.getType());

In versions of FastAPI before 0.99.0 (0.99.0 and above use the newer OpenAPI 3.1.0) when you used `example` or `examples` with any of the other utilities (`Query()`, `Body()`, etc.) those examples were not added to the JSON Schema that describes that data (not even to OpenAPI's own version of JSON Schema), they were added directly to the *path operation* declaration in OpenAPI (outside the parts of OpenAPI that use JSON Schema).

<pre>
buffer := [10]string{}             // len(buffer) == 10
intSet := [6]int{1, 2, 3, 5}       // len(intSet) == 6
days := [...]string{"Sat", "Sun"}  // len(days) == 2
</pre>

<p>
A slice literal describes the entire underlying array literal.
Thus the length and capacity of a slice literal are the maximum
element index plus one. A slice literal has the form
</p>

<pre>
[]T{x1, x2, … xn}
</pre>

- This PR corrects that documentation, making it clear to users that podSelector is optional and describes its default behavior. ([#131354](https://github.com/kubernetes/kubernetes/pull/131354), [@tomoish](https://github.com/tomoish)) [SIG Network]

### Feature

*   TensorFlow pip packages are now built with CUDA11.2 and cuDNN 8.1.0

## Breaking Changes

*   The `TF_CPP_MIN_VLOG_LEVEL` environment variable has been renamed to
    `TF_CPP_MAX_VLOG_LEVEL` which correctly describes its effect.

## Bug Fixes and Other Changes

*   `tf.keras`:

    *   Preprocessing layers API consistency changes:
        *   `StringLookup` added `output_mode`, `sparse`, and

Esa información extra se añadirá tal cual al **JSON Schema** resultante para ese modelo, y se usará en la documentación de la API.

Puedes usar el atributo `model_config` que toma un `dict` como se describe en [Documentación de Pydantic: Configuración](https://docs.pydantic.dev/latest/api/config/).

Y tu aplicación de **FastAPI** también podría estar compuesta de varios archivos/módulos, etc.

### Archivo de aplicación **FastAPI** { #fastapi-app-file }

Digamos que tienes una estructura de archivos como se describe en [Aplicaciones Más Grandes](bigger-applications.md):

```
.
├── app
│   ├── __init__.py
│   └── main.py
```

En el archivo `main.py` tienes tu aplicación de **FastAPI**:

* `C:\Program Files\Python312\Scripts`
* `C:\Program Files\Python312`
* `C:\Windows\System32`

////

Cuando escribes un **comando** en la terminal, el sistema operativo **busca** el programa en **cada uno de esos directorios** listados en la variable de entorno `PATH`.

Por ejemplo, cuando escribes `python` en la terminal, el sistema operativo busca un programa llamado `python` en el **primer directorio** de esa lista.