p2","value":"off"}]},"region":{"_":[{"key":"name","value":""}]},"scanner":{"_":[{"key":"speed","value":"default"},{"key":"idle_speed","value":""},{"key":"alert_excess_versions","value":"100"},{"key":"alert_excess_folders","value":"50000"},{"key":"delay","value":""},{"key":"max_wait","value":""},{"key":"cycle","value":""}]},"site":{"_":[{"key":"name","value":""},{"key":"region","value":""}]},"storage_class":{"_":[{"key":"standard","value":"EC:5"},{"key":"rrs","value":"EC:1"},{"key":"optimize","va...

  }

  @Test fun test() {
    val t1 = System.nanoTime() / 1e6

    val delays = mutableListOf(TimeUnit.MILLISECONDS.toNanos(1000), -1L)
    queue.schedule("task", TimeUnit.MILLISECONDS.toNanos(750)) {
      log.put("runOnce delays.size=${delays.size}")
      return@schedule delays.removeAt(0)
    }

    assertThat(log.take()).isEqualTo("runOnce delays.size=2")
    val t2 = System.nanoTime() / 1e6 - t1

* Bound cloud allocator to 10 retries with 100 ms delay between retries. ([#61375](https://github.com/kubernetes/kubernetes/pull/61375), [@satyasm](https://github.com/satyasm))

## Changelog since v1.22.9

## Changes by Kind

### Bug or Regression

- Correct event registration for multiple scheduler plugins; this fixes a potential significant delay in re-queueing unschedulable pods. ([#109447](https://github.com/kubernetes/kubernetes/pull/109447), [@ahg-g](https://github.com/ahg-g)) [SIG Scheduling and Testing]

    timeToFirstByte()
  }

  /**
   * Test to confirm that events are reported at the time they occur and no earlier and no later.
   * This inserts a bunch of synthetic 250 ms delays into both client and server and confirms that
   * the same delays make it back into the events.
   *
   * We've had bugs where we report an event when we request data rather than when the data actually

* **Deep Learning**: Esse é um subcampo do Aprendizado de Máquina, então, o mesmo se aplica. A diferença é que não há apenas uma grande planilha com números para multiplicar, mas um grande conjunto delas, e em muitos casos, você utiliza um processador especial para construir e/ou usar esses modelos.

### Concorrência + Paralelismo: Web + Aprendizado de Máquina { #concurrency-parallelism-web-machine-learning }

Bu işlem için, `TestClient`'ı bir `with` ifadesinde kullanarak WebSocket'e bağlanabilirsiniz:

{* ../../docs_src/app_testing/tutorial002.py hl[27:31] *}

/// note | Not

Daha fazla detay için Starlette'in <a href="https://www.starlette.dev/staticfiles/" class="external-link" target="_blank">Websockets'i Test Etmek</a> dokümantasyonunu inceleyin.

- Fix missing kubelet_volume_stats_* metrics ([#133890](https://github.com/kubernetes/kubernetes/pull/133890), [@huww98](https://github.com/huww98)) [SIG Instrumentation and Node]
- Fix occasional schedule delay when the static PV is created ([#133929](https://github.com/kubernetes/kubernetes/pull/133929), [@huww98](https://github.com/huww98)) [SIG Scheduling and Storage]

  The other guests had taken advantage of the Queen's absence,
and were resting in the shade:  however, the moment they saw her,
they hurried back to the game, the Queen merely remarking that a
moment's delay would cost them their lives.

  All the time they were playing the Queen never left off
quarrelling with the other players, and shouting `Off with his
head!' or `Off with her head!'  Those whom she sentenced were

/// tip | Dica

As próximas seções **não são necessariamente "avançadas"**.

E é possível que para o seu caso de uso, a solução está em uma delas.

///

## Leia o Tutorial primeiro { #read-the-tutorial-first }