https://davidefiocco.github.io/streamlit-fastapi-ml-serving/ title: Machine learning model serving in Python using FastAPI and streamlit - author: Netflix author_link: https://netflixtechblog.com/ link: https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072 title: Introducing Dispatch - author: Stavros Korokithakis author_link: https://twitter.com/Stavros link: https://www.stavros.io/posts/fastapi-with-django/ title: Using FastAPI with Django - author: Twilio author_link: https://www.twilio.com link: https...

<div style="text-align: right; margin-right: 10%;">Kevin Glisson, Marc Vilanova, Forest Monsen - <strong>Netflix</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(ref)</small></a></div>

---

   * #monitor}.
   */
  private void dispatchListenerEvents() {
    if (!monitor.isOccupiedByCurrentThread()) {
      listeners.dispatch();
    }
  }

  private void enqueueStartingEvent() {
    listeners.enqueue(STARTING_EVENT);
  }

  private void enqueueRunningEvent() {
    listeners.enqueue(RUNNING_EVENT);
  }

"_**Netflix** a le plaisir d'annoncer la sortie en open-source de notre framework d'orchestration de **gestion de crise** : **Dispatch** ! [construit avec **FastAPI**]_"

<div style="text-align: right; margin-right: 10%;">Kevin Glisson, Marc Vilanova, Forest Monsen - <strong>Netflix</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(ref)</small></a></div>

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"_**Netflix** 很榮幸地宣布開源**危機管理**協調框架： **Dispatch**! [是使用 **FastAPI** 建構]_"

<div style="text-align: right; margin-right: 10%;">Kevin Glisson, Marc Vilanova, Forest Monsen - <strong>Netflix</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(ref)</small></a></div>

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"_我對 **FastAPI** 興奮得不得了。它太有趣了！_"

  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  EXPECT_FALSE(executed);
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);

  // Custom devices can refuse to do type-based dispatch (as hcustom1 is
  // configured to do)
  matmul.reset(MatMulOp(context.get(), hcustom1.get(), hcpu.get()));
  num_retvals = 1;
  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());

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"_**Netflix** is pleased to announce the open-source release of our **crisis management** orchestration framework: **Dispatch**! [built with **FastAPI**]_"

<div style="text-align: right; margin-right: 10%;">Kevin Glisson, Marc Vilanova, Forest Monsen - <strong>Netflix</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(ref)</small></a></div>

---

   * #monitor}.
   */
  private void dispatchListenerEvents() {
    if (!monitor.isOccupiedByCurrentThread()) {
      listeners.dispatch();
    }
  }

  private void enqueueStartingEvent() {
    listeners.enqueue(STARTING_EVENT);
  }

  private void enqueueRunningEvent() {
    listeners.enqueue(RUNNING_EVENT);
  }

   * {@link MoreExecutors#directExecutor}. Normally, when the first future completes, all the other
   * tasks would be called recursively. Here, we detect that the delegate executor is executing
   * inline, and maintain a queue to dispatch tasks iteratively. There is one instance of this class
   * per call to submit() or submitAsync(), and each instance supports only one call to execute().
   *

   * {@link MoreExecutors#directExecutor}. Normally, when the first future completes, all the other
   * tasks would be called recursively. Here, we detect that the delegate executor is executing
   * inline, and maintain a queue to dispatch tasks iteratively. There is one instance of this class
   * per call to submit() or submitAsync(), and each instance supports only one call to execute().
   *