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  1. docs/pt/docs/deployment/server-workers.md

    ```
    
    </div>
    
    ////
    
    A única opção nova aqui é `--workers` informando ao Uvicorn para iniciar 4 processos de trabalho.
    
    Você também pode ver que ele mostra o **PID** de cada processo, `27365` para o processo pai (este é o **gerenciador de processos**) e um para cada processo de trabalho: `27368`, `27369`, `27370` e `27367`.
    
    ## Conceitos de Implantação
    
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  2. cmd/metrics-v3-system-process.go

    	processIOReadBytesMD              = NewCounterMD(processIOReadBytes, "Total bytes read by the process from the underlying storage system, /proc/[pid]/io read_bytes")
    Registered: Sun Nov 03 19:28:11 UTC 2024
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  3. build-logic/cleanup/src/main/java/gradlebuild/cleanup/services/KillLeakingJavaProcesses.java

            try {
                Process process = new ProcessBuilder().command(args).start();
                CountDownLatch latch = new CountDownLatch(2);
                ByteArrayOutputStream stdout = connectStream(process.getInputStream(), latch);
                ByteArrayOutputStream stderr = connectStream(process.getErrorStream(), latch);
    
                process.waitFor(1, TimeUnit.MINUTES);
    Registered: Wed Nov 06 11:36:14 UTC 2024
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  4. docs/pt/docs/deployment/concepts.md

    Isso ainda é verdade.
    
    Então, para poder ter **vários processos** ao mesmo tempo, tem que haver um **único processo escutando em uma porta** que então transmite a comunicação para cada processo de trabalho de alguma forma.
    
    ### Memória por Processo
    
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  5. docs/pt/docs/deployment/manually.md

    Esta é a ideia básica. Mas você provavelmente vai querer cuidar de algumas coisas adicionais, como:
    
    * Segurança - HTTPS
    * Executando na inicialização
    * Reinicializações
    * Replicação (o número de processos em execução)
    * Memória
    * Passos anteriores antes de começar
    
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  6. SECURITY.md

    ## Untrusted inputs during training and prediction
    
    TensorFlow supports a wide range of input data formats. For example it can
    process images, audio, videos, and text. There are several modules specialized
    in taking those formats, modifying them, and/or converting them to intermediate
    formats that can be processed by TensorFlow.
    
    These modifications and conversions are handled by a variety of libraries that
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  7. docs/pt/docs/tutorial/background-tasks.md

    - Processando dados:
      - Por exemplo, digamos que você receba um arquivo que deve passar por um processo lento, você pode retornar uma resposta de "Aceito" (HTTP 202) e processá-lo em segundo plano.
    
    ## Usando `BackgroundTasks`
    
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  8. docs/en/docs/deployment/concepts.md

    ### Multiple Processes - An Example
    
    In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.
    
    This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.
    
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  9. docs/en/docs/deployment/server-workers.md

    ```
    
    </div>
    
    ////
    
    The only new option here is `--workers` telling Uvicorn to start 4 worker processes.
    
    You can also see that it shows the **PID** of each process, `27365` for the parent process (this is the **process manager**) and one for each worker process: `27368`, `27369`, `27370`, and `27367`.
    
    ## Deployment Concepts
    
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  10. docs/en/docs/deployment/docker.md

    A container is running as long as the **main process** (command or program) is running.
    
    A container normally has a **single process**, but it's also possible to start subprocesses from the main process, and that way you will have **multiple processes** in the same container.
    
    But it's not possible to have a running container without **at least one running process**. If the main process stops, the container stops.
    
    Registered: Sun Nov 03 07:19:11 UTC 2024
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