* to the build service.
 */
interface TestFilesCleanupBuildServiceRootExtension {
    val projectStates: MapProperty<String, TestFilesCleanupProjectState>

    /**
     * Key is the path of a task, value is the possible report dirs it generates.
     */
    val taskPathToReports: MapProperty<String, List<File>>

0002 0.554 responseBodyEnd
0002 0.554 connectionReleased
0002 0.554 callEnd
0001 0.624 responseBodyEnd
0001 0.624 connectionReleased
0001 0.624 callEnd
```

The `EventListener.Factory` also makes it possible to limit metrics to a subset of calls. This one captures metrics on a random 10%:

```java
class MetricsEventListener extends EventListener {
  private static final Factory FACTORY = new Factory() {

////

//// tab | Python 3.10+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python
{!> ../../docs_src/app_testing/app_b_py310/main.py!}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python
{!> ../../docs_src/app_testing/app_b/main.py!}
```

////

{!../../docs_src/response_directly/tutorial002.py!}
```

## Notas

Cuando devuelves una `Response` directamente, los datos no son validados, convertidos (serializados), ni documentados automáticamente.

Pero todavía es posible documentarlo como es descrito en [Respuestas adicionales en OpenAPI](additional-responses.md){.internal-link target=_blank}.

In the next sections you will see other options, configurations, and additional features.

/// tip

The next sections are **not necessarily "advanced"**.

And it's possible that for your use case, the solution is in one of them.

///

## Read the Tutorial first

## Current Behavior
<!--- If describing a bug, tell us what happens instead of the expected behavior -->
<!--- If suggesting a change/improvement, explain the difference from current behavior -->

## Possible Solution
<!--- Not obligatory, but suggest a fix/reason for the bug, -->
<!--- or ideas how to implement the addition or change -->

## Steps to Reproduce (for bugs)

////

//// tab | Python 3.8+

```Python
{!> ../../docs_src/security/tutorial001_an.py!}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python
{!> ../../docs_src/security/tutorial001.py!}
```

////

## Run it

/// info

stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running

		Method: http.MethodPost,
		URL:    u,
	}
	if !guessIsRPCReq(r) {
		t.Fatal("Test shouldn't fail for a possible net/rpc request.")
	}
	r = &http.Request{
		Proto:  "HTTP/1.1",
		Method: http.MethodGet,
		URL:    u,
	}
	if !guessIsRPCReq(r) {
		t.Fatal("Test shouldn't fail for a possible net/rpc request.")
	}
	r = &http.Request{
		Proto:  "HTTP/1.1",
		Method: http.MethodGet,

But at some point, there was no other option than creating something that provided all these features, taking the best ideas from previous tools, and combining them in the best way possible, using language features that weren't even available before (Python 3.6+ type hints).

</blockquote>

## Investigation