/**
 * Align with build-logic/cleanup/src/main/java/gradlebuild/cleanup/services/KillLeakingJavaProcesses.java
 */
enum class KillProcessMode {
    KILL_LEAKED_PROCESSES_FROM_PREVIOUS_BUILDS,
    KILL_PROCESSES_STARTED_BY_GRADLE,
    KILL_ALL_GRADLE_PROCESSES
}

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.

**Note**: You can mix `def` and `async def` in your *path operation functions* as much as you need and define each one using the best option for you. FastAPI will do the right thing with them.

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details

* The interactive API documentation will be automatically updated, including the new body:

![Swagger UI](https://fastapi.tiangolo.com/img/index/index-03-swagger-02.png)

* Click on the button "Try it out", it allows you to fill the parameters and directly interact with the API:

```Python hl_lines="2  7"
{!../../../docs_src/custom_response/tutorial001b.py!}
```

!!! info
    The parameter `response_class` will also be used to define the "media type" of the response.

    In this case, the HTTP header `Content-Type` will be set to `application/json`.

    And it will be documented as such in OpenAPI.

!!! tip
    The `ORJSONResponse` is currently only available in FastAPI, not in Starlette.

    /**
     * Sets the minimum number of seconds that a response will continue to be fresh for. If the
     * response will be stale when [minFresh] have elapsed, the cached response will not be used and
     * a network request will be made.
     *
     * @param minFresh a non-negative integer. This is stored and transmitted with
     *     [TimeUnit.SECONDS] precision; finer precision will be lost.
     */
    fun minFresh(
      minFresh: Int,

  // The maximum time in seconds for a deployment to make progress before it
  // is considered to be failed. The deployment controller will continue to
  // process failed deployments and a condition with a ProgressDeadlineExceeded
  // reason will be surfaced in the deployment status. Note that progress will
  // not be estimated during the time a deployment is paused. Defaults to 600s.
  optional int32 progressDeadlineSeconds = 9;
}

  // is considered to be failed. The deployment controller will continue to
  // process failed deployments and a condition with a ProgressDeadlineExceeded
  // reason will be surfaced in the deployment status. Note that progress will
  // not be estimated during the time a deployment is paused. This is set to
  // the max value of int32 (i.e. 2147483647) by default, which means "no deadline".
  // +optional

So, we create an additional dependency `get_current_active_user` that in turn uses `get_current_user` as a dependency.

Both of these dependencies will just return an HTTP error if the user doesn't exist, or if is inactive.

So, in our endpoint, we will only get a user if the user exists, was correctly authenticated, and is active:

=== "Python 3.10+"

    ```Python hl_lines="58-66  69-74  94"

   * until one is ready. If there are no ready queues, or if other threads have everything under
   * control this will return null. If there is more than a single task ready to execute immediately
   * this will start another thread to handle that work.
   */
  fun awaitTaskToRun(): Task? {
    lock.assertHeld()

    while (true) {
      if (readyQueues.isEmpty()) {