## Gunicorn mit Uvicorn-Workern ausführen

Dann können Sie Gunicorn ausführen mit:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511

        ```

     * 因此，`main:app` 中的冒号相当于 `from main import app` 中的 Python `import` 部分。

* `--workers`：要使用的worker进程数量，每个进程将运行一个 Uvicorn worker进程，在本例中为 4 个worker进程。

* `--worker-class`：在worker进程中使用的与 Gunicorn 兼容的工作类。
     * 这里我们传递了 Gunicorn 可以导入和使用的类：

         ```Python
         import uvicorn.workers.UvicornWorker
         ```

* `--bind`：这告诉 Gunicorn 要监听的 IP 和端口，使用冒号 (`:`) 分隔 IP 和端口。

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514

  BasicTestsForTwoDevices(context.get(),
                          "/job:worker/replica:0/task:1/device:CPU:0",
                          "/job:worker/replica:0/task:2/device:CPU:0");

  worker_server1.release();
  worker_server2.release();
}

TEST(PARALLEL_DEVICE, TestAsyncCopyOff) {
  std::unique_ptr<TFE_ContextOptions, decltype(&TFE_DeleteContextOptions)> opts(

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(

default            reviews-v3-5b9bd44f4-z9ms4                           10.244.1.43 ambient-worker        None                                HBONE
default            sleep-7656cf8794-lxcmx                               10.244.2.58 ambient-worker2       None                                HBONE

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514

* **Uvicorn** managing **Uvicorn 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**

  //  Worker0:
  //  cluster { job { name: "client" tasks { key: 0 value: "localhost:14526" } }
  //            job { name: "worker" tasks { key: 0 value: "localhost:14522" } }
  //          } job_name: "worker" protocol: "grpc"
  //

  // Create `worker_1` using single host server def `worker_1_server_def`.
  tensorflow::ServerDef worker_1_server_def =
      CreateSingleHostServerDef(cluster_server_def, 1);