participant code as Code
participant function as say_hi()
participant execute as Funktion ausgeführt

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: führe Code der Funktion aus
        execute ->> code: gib das Resultat zurück
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")

participant execute as Execute function

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: execute function code
        execute ->> code: return the result
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end

    rect rgba(0, 255, 0, .1)

participant execute as Execute function

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: 执行函数代码
        execute ->> code: 返回结果
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: 返回存储的结果
    end

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Rick")

participant execute as Execute function

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: execute function code
        execute ->> code: return the result
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end

    rect rgba(0, 255, 0, .1)

## **FastAPI** auf GitHub einen Stern geben

Sie können FastAPI auf GitHub „starren“ (durch Klicken auf den Stern-Button oben rechts): <a href="https://github.com/tiangolo/fastapi" class="external-link" target="_blank">https://github.com/tiangolo/fastapi</a>. ⭐️

                         tensorflow::FunctionLibraryDefinition* flib_def,
                         std::vector<std::string>* control_ret_node_names,
                         bool* control_rets_updated) override {
    // Inject failure to function instantiation if finding a node that contains
    // the given node name (error_node_) and requested device (error_device_).
    for (const auto node : graph->get()->nodes()) {

  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph
  // functions, and their send/recvs corountines).
  config.set_inter_op_parallelism_threads(1);

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(config, ret));
  return ret;
}