}
		nextFiles = next
	}

	for _, c := range contexts {
		c.Compiler = build.Default.Compiler
	}

	walkers := make([]*Walker, len(contexts))
	var wg sync.WaitGroup
	for i, context := range contexts {
		wg.Add(1)
		go func() {
			defer wg.Done()
			walkers[i] = NewWalker(context, filepath.Join(testenv.GOROOT(t), "src"))
		}()
	}
	wg.Wait()

///

## Несколько воркеров { #multiple-workers }

Можно запустить несколько воркеров с помощью опции командной строки `--workers`:

//// tab | `fastapi`

Если вы используете команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

///

## Кілька працівників { #multiple-workers }

Ви можете запустити кілька працівників за допомогою параметра командного рядка `--workers`:

//// tab | `fastapi`

Якщо ви використовуєте команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

load, number of objects in the object store as well as storage speed. In addition, any bandwidth limits set via `mc admin bucket remote add` could also contribute to replication speed. The number of workers used for replication defaults to 100. Based on network bandwidth and system load, the number of workers used in replication can be configured using `mc admin config set alias api` to set the `replication_workers`. The prometheus metrics exposed by MinIO can be used to plan resource allocation and bandwidth...

import org.gradle.api.tasks.PathSensitive;
import org.gradle.api.tasks.PathSensitivity;
import org.gradle.api.tasks.SkipWhenEmpty;
import org.gradle.api.tasks.TaskAction;
import org.gradle.workers.WorkAction;
import org.gradle.workers.WorkParameters;
import org.gradle.workers.WorkerExecutor;

import javax.inject.Inject;
import java.io.File;
import java.io.IOException;
import java.io.UncheckedIOException;
import java.nio.file.FileSystem;

TF_CAPI_EXPORT extern TFE_ContextDevicePlacementPolicy
TFE_ContextGetDevicePlacementPolicy(TFE_Context* ctx);

// A tensorflow.ServerDef specifies remote workers (in addition to the current
// workers name). Operations created in this context can then be executed on
// any of these remote workers by setting an appropriate device.
//
// If the following is set, all servers identified by the
// ServerDef must be up when the context is created.

	oi, ok := oiCache[fmt.Sprintf("%s-%s", toDel.ObjectName, toDel.VersionID)]
	return oi, ok
}

func batchObjsForDelete(ctx context.Context, r *BatchJobExpire, ri *batchJobInfo, job BatchJobRequest, api ObjectLayer, wk *workers.Workers, expireCh <-chan []expireObjInfo) {
	vc, _ := globalBucketVersioningSys.Get(r.Bucket)
	retryAttempts := job.Expire.Retry.Attempts
	if retryAttempts <= 0 {
		retryAttempts = batchExpireJobDefaultRetries
	}

| `minio_node_replication_average_active_workers`         | Average number of active replication workers                                                             |
| `minio_node_replication_max_active_workers`             | Maximum number of active replication workers seen since server start                                     |

	es.mu.Lock()
	defer es.mu.Unlock()
	var workers []chan expiryOp
	if v := es.workers.Load(); v != nil {
		// Copy to new array.
		workers = append(workers, *v...)
	}

	if n == len(workers) || n < 1 {
		return
	}

	for len(workers) < n {
		input := make(chan expiryOp, 10000)
		workers = append(workers, input)
		go es.Worker(input)
		es.stats.workers.Add(1)
	}

	for len(workers) > n {

    <!-- These packages are duplicated in workers and daemon-server-worker, don't require a package-info.java in each place -->
    <suppress checks="JavadocPackage"
              files=".*[/\\]platforms[/\\]core-execution[/\\]daemon-server-worker[/\\]src[/\\]main[/\\]java[/\\]org[/\\]gradle[/\\]workers[/\\][^/\\]+"/>

    <!-- These packages are duplicated in code-quality and code-quality-workers, don't require a package-info.java in each place -->