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src/cmd/api/main_test.go
} nextFiles = next } for _, c := range contexts { c.Compiler = build.Default.Compiler } walkers := make([]*Walker, len(contexts)) var wg sync.WaitGroup for i, context := range contexts { i, context := i, context wg.Add(1) go func() { defer wg.Done() walkers[i] = NewWalker(context, filepath.Join(testenv.GOROOT(t), "src")) }() } wg.Wait()
Registered: Tue Oct 29 11:13:09 UTC 2024 - Last Modified: Wed Sep 04 18:16:59 UTC 2024 - 31.4K bytes - Viewed (0) -
docs/em/docs/deployment/server-workers.md
## 🏃 🐁 ⏮️ Uvicorn 👨🏭 ⤴️ 👆 💪 🏃 🐁 ⏮️: <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 [19513] [INFO] Booting worker with pid: 19513
Registered: Sun Oct 27 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 8.2K bytes - Viewed (0) -
docs/zh/docs/deployment/server-workers.md
这将安装带有`standard`扩展包(以获得高性能)的 Uvicorn 和 Gunicorn。 ## Run Gunicorn with Uvicorn Workers 接下来你可以通过以下命令运行Gunicorn: <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
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docs/en/docs/deployment/server-workers.md
In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter. /// ## Multiple Workers You can start multiple workers with the `--workers` command line option: //// tab | `fastapi` If you use the `fastapi` command: <div class="termy">
Registered: Sun Oct 27 07:19:11 UTC 2024 - Last Modified: Wed Sep 18 16:09:57 UTC 2024 - 8.7K bytes - Viewed (0) -
docs/de/docs/deployment/server-workers.md
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 [19513] [INFO] Booting worker with pid: 19513
Registered: Sun Oct 27 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 10.1K bytes - Viewed (0) -
docs/ko/docs/deployment/server-workers.md
## 구니콘을 유비콘 워커와 함께 실행하기 설치 후 구니콘 실행하기: <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 [19513] [INFO] Booting worker with pid: 19513
Registered: Sun Oct 27 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 10.2K bytes - Viewed (0) -
docs/pt/docs/deployment/server-workers.md
/// ## Vários trabalhadores Você pode iniciar vários trabalhadores com a opção de linha de comando `--workers`: //// tab | `fastapi` Se você usar o comando `fastapi`: <div class="termy"> ```console $ <pre> <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:single">main.py</u> <font color="#3465A4">INFO </font> Using path <font color="#3465A4">main.py</font>
Registered: Sun Oct 27 07:19:11 UTC 2024 - Last Modified: Fri Sep 20 11:01:03 UTC 2024 - 9K bytes - Viewed (0) -
docs/ja/docs/deployment/server-workers.md
Gunicornを以下のように起動させることができます: <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 [19513] [INFO] Booting worker with pid: 19513
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docs/metrics/v3.md
Registered: Sun Oct 27 19:28:09 UTC 2024 - Last Modified: Fri Aug 02 22:30:11 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/c/eager/c_api.h
TF_CAPI_EXPORT extern TFE_ContextDevicePlacementPolicy TFE_ContextGetDevicePlacementPolicy(TFE_Context* ctx); // A tensorflow.ServerDef specifies remote workers (in addition to the current // workers name). Operations created in this context can then be executed on // any of these remote workers by setting an appropriate device. // // If the following is set, all servers identified by the // ServerDef must be up when the context is created.
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Thu Apr 27 21:07:00 UTC 2023 - 22.8K bytes - Viewed (0)