// Return a shape op fetching the shape of `a`.
TFE_Op* ShapeOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return an allreduce op adding up input tensor `in` from `group_size` workers.
TFE_Op* AllReduceOp(TFE_Context* ctx, TFE_TensorHandle* in, int group_size);

// Return a SendOp op `op_name` with send input tensor `in` and attributes
// `send_device`, `recv_device`, and `send_device_incarnation` set.

	}

	workerSize, err := strconv.Atoi(env.Get("_MINIO_BATCH_KEYROTATION_WORKERS", strconv.Itoa(runtime.GOMAXPROCS(0)/2)))
	if err != nil {
		return err
	}

	wk, err := workers.New(workerSize)
	if err != nil {
		// invalid worker size.
		return err
	}

	ctx, cancel := context.WithCancel(ctx)

	results := make(chan itemOrErr[ObjectInfo], 100)

  /**
   * This counter prevents an ABA issue where a thread may successfully schedule the worker, the
   * worker runs and exhausts the queue, another thread enqueues a task and fails to schedule the
   * worker, and then the first thread's call to delegate.execute() returns. Without this counter,
   * it would observe the QUEUING state and set it to QUEUED, and the worker would never be
   * scheduled again for future submissions.
   */
  @GuardedBy("queue")

  /**
   * This counter prevents an ABA issue where a thread may successfully schedule the worker, the
   * worker runs and exhausts the queue, another thread enqueues a task and fails to schedule the
   * worker, and then the first thread's call to delegate.execute() returns. Without this counter,
   * it would observe the QUEUING state and set it to QUEUED, and the worker would never be
   * scheduled again for future submissions.
   */
  @GuardedBy("queue")

    <img src="https://github.com/fastapi/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

        subprojectName.contains("native") ||
            // Include precondition-tester here so we understand that tests do run on macOS intel as well
            subprojectName in listOf("file-watching", "snapshots", "workers", "logging", "precondition-tester")
    } else {
        true
    }

func (m *rateMeasurement) getExpMovingAvgBytesPerSecond() float64 {
	m.lock.Lock()
	defer m.lock.Unlock()
	return m.expMovingAvg
}

// ActiveWorkerStat is stat for active replication workers
type ActiveWorkerStat struct {
	Curr int     `json:"curr"`
	Avg  float32 `json:"avg"`
	Max  int     `json:"max"`
	hist metrics.Histogram
}

func newActiveWorkerStat(r metrics.Registry) *ActiveWorkerStat {

| `minio_cluster_usage_buckets_versions_count`                    | Total object versions count in bucket, including delete markers. <br><br>Type: gauge | `bucket`          |
| `minio_cluster_usage_buckets_delete_markers_count`              | Total delete markers count in bucket. <br><br>Type: gauge                            | `bucket`          |

// once (i.e., on the main function side) in running distributed functions.
// This test creates a cluster with two workers, create a variable on the
// second worker, and run a distributed function (VariableAddFunction) whose ops
// span the local and remote workers. If the graph optimization pass is executed
// on both the main function side and the component function side, an error will

* Modèles **SQLAlchemy** (indépendants des extensions Flask, afin qu'ils puissent être utilisés directement avec des *workers* Celery).
* Modèle de démarrages basiques pour les utilisateurs (à modifier et supprimer au besoin).
* Migrations **Alembic**.
* **CORS** (partage des ressources entre origines multiples, ou *Cross Origin Resource Sharing*).
* *Worker* **Celery** pouvant importer et utiliser les modèles et le code du reste du backend.