int port = tensorflow::testing::PickUnusedPortOrDie();
  // 3. Replace worker1 with a new worker in server_def_0 and server_def_1.
  ReplaceTaskInServerDef(&server_def_0, /*task_index=*/1, "localhost", port);
  ReplaceTaskInServerDef(&server_def_1, /*task_index=*/1, "localhost", port);
  // 4. Start a new task to replace worker1.
  server_def_0.set_task_index(1);
  worker_server1.release();

///

## Несколько воркеров { #multiple-workers }

Можно запустить несколько воркеров с помощью опции командной строки `--workers`:

//// tab | `fastapi`

Если вы используете команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

///

## Кілька працівників { #multiple-workers }

Ви можете запустити кілька працівників за допомогою параметра командного рядка `--workers`:

//// tab | `fastapi`

Якщо ви використовуєте команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

		// If the channel reaches above half capacity
		// we spawn more workers. The workers spawned
		// from this main worker routine will exit
		// once the channel drops below half capacity
		// and when it's been at least 30 seconds since
		// we launched a new worker.
		if mainWorker && len(h.logCh) > cap(h.logCh)/2 {
			nWorkers := h.workers.Load()
			if nWorkers < h.maxWorkers {
				if time.Since(h.lastStarted).Milliseconds() > 10 {

COPY ./app /code/app

# (1)!
CMD ["fastapi", "run", "app/main.py", "--port", "80", "--workers", "4"]
```

1. Hier verwenden wir die `--workers` Befehlszeilenoption, um die Anzahl der Worker auf 4 festzulegen.

Hier sind einige Beispiele, wann das sinnvoll sein könnte:

#### Eine einfache Anwendung { #a-simple-app }

    <!-- These packages are duplicated in workers and daemon-server-worker, don't require a package-info.java in each place -->
    <suppress checks="JavadocPackage"
              files=".*[/\\]platforms[/\\]core-execution[/\\]daemon-server-worker[/\\]src[/\\]main[/\\]java[/\\]org[/\\]gradle[/\\]workers[/\\][^/\\]+"/>

    <!-- These packages are duplicated in code-quality and code-quality-workers, don't require a package-info.java in each place -->

    "crossVersionTests": false
  },
  {
    "name": "scala-compiler-worker",
    "path": "platforms/jvm/scala-compiler-worker",
    "unitTests": false,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "scaladoc-worker",
    "path": "platforms/jvm/scaladoc-worker",
    "unitTests": false,
    "functionalTests": false,
    "crossVersionTests": false

		workers = workers[:len(workers)-1]
		worker <- expiryOp(nil)
		es.stats.workers.Add(-1)
	}
	// Atomically replace workers.
	es.workers.Store(&workers)
}

// Worker handles 4 types of expiration tasks.
// 1. Expiry of objects, includes regular and transitioned objects
// 2. Expiry of noncurrent versions due to NewerNoncurrentVersions

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

COPY ./app /code/app

# (1)!
CMD ["fastapi", "run", "app/main.py", "--port", "80", "--workers", "4"]
```

1. Burada worker sayısını 4 yapmak için `--workers` komut satırı seçeneğini kullanıyoruz.

Bunun mantıklı olabileceği birkaç örnek:

#### Basit Bir Uygulama { #a-simple-app }

Here are some possible combinations and strategies:

* **Uvicorn** with `--workers`
    * One Uvicorn **process manager** would listen on the **IP** and **port**, and it would start **multiple Uvicorn worker processes**.
* **Kubernetes** and other distributed **container systems**