TF_NewStatus(), TF_DeleteStatus);
  std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> context(
      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  tensorflow::ServerDef server_def = GetServerDef("worker", 3);

  // This server def has the task index set to 0.
  std::string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;

		// If the channel reaches above half capacity
		// we spawn more workers. The workers spawned
		// from this main worker routine will exit
		// once the channel drops below half capacity
		// and when it's been at least 30 seconds since
		// we launched a new worker.
		if mainWorker && len(h.logCh) > cap(h.logCh)/2 {
			nWorkers := h.workers.Load()
			if nWorkers < h.maxWorkers {
				if time.Since(h.lastStarted).Milliseconds() > 10 {

    )

    failureConditions {
        // JavaExecDebugIntegrationTest.debug session fails without debugger might cause JVM crash
        // Some soak tests produce OOM exceptions
        // There are also random worker crashes for some tests.
        // We have test-retry to handle the crash in tests
        javaCrash = false
    }
})

private fun determineFlakyTestStrategy(stage: Stage): String {

<div class="termy">

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Run with Trio

然后你可以传递值`trio`给命令行选项`--worker-class`:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

这将通过您的应用程序启动 Hypercorn，并使用 Trio 作为后端。

现在您可以在应用程序内部使用 Trio。 或者更好的是，您可以使用 AnyIO，使您的代码与 Trio 和 asyncio 兼容。 🎉

## 部署概念

// EagerService to maintain consistency between client and worker. The
// context_id is initialized with a dummy value and is later set when the worker
// is initialized (either locally or remotely). The context_id can change during
// the process lifetime although this should cause the worker to be
// reinitialized (e.g. cleared caches) as well.

	if (checkOld > 0 && len(p.workers) != checkOld) || n == len(p.workers) || n < 1 {
		// Either already satisfied or worker count changed while we waited for the lock.
		return
	}
	for len(p.workers) < n {
		input := make(chan ReplicationWorkerOperation, 10000)
		p.workers = append(p.workers, input)

		go p.AddWorker(input, &p.activeWorkers)
	}
	for len(p.workers) > n {
		worker := p.workers[len(p.workers)-1]

type ReplicationStats struct {
	// map of site deployment ID to site replication status
	// for site replication - maintain stats at global level
	srStats *SRStats
	// active worker stats
	workers *ActiveWorkerStat
	// queue stats cache
	qCache queueCache

	pCache proxyStatsCache
	// mrf backlog stats
	mrfStats ReplicationMRFStats
	// for bucket replication, continue to use existing cache

                    <mxGeometry relative="1" as="geometry"/>
                </mxCell>
                <mxCell id="12" value="&lt;font face=&quot;roboto&quot;&gt;&lt;span style=&quot;font-size: 24px&quot;&gt;Worker Process&lt;/span&gt;&lt;/font&gt;" style="shape=hexagon;perimeter=hexagonPerimeter2;whiteSpace=wrap;html=1;fixedSize=1;strokeWidth=3;fillColor=#fff2cc;strokeColor=#d6b656;" parent="1" vertex="1">

    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "worker-main",
    "path": "platforms/core-execution/worker-main",
    "unitTests": true,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "workers",
    "path": "platforms/core-execution/workers",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false

HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->nextInt(I)I
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->pollGlobalQueues()Lkotlinx/coroutines/scheduling/Task;
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->run()V
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->setIndexInArray(I)V
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->setNextParkedWorker(Ljava/lang/Object;)V