workers = workers[:len(workers)-1]
		worker <- expiryOp(nil)
		es.stats.workers.Add(-1)
	}
	// Atomically replace workers.
	es.workers.Store(&workers)
}

// Worker handles 4 types of expiration tasks.
// 1. Expiry of objects, includes regular and transitioned objects
// 2. Expiry of noncurrent versions due to NewerNoncurrentVersions

    "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

// newBatchJobPool creates a pool of job manifest workers of specified size
func newBatchJobPool(ctx context.Context, o ObjectLayer, workers int) *BatchJobPool {
	jpool := &BatchJobPool{
		ctx:          ctx,
		objLayer:     o,
		jobCh:        make(chan *BatchJobRequest, 10000),
		workerKillCh: make(chan struct{}, workers),
		jobCancelers: make(map[string]context.CancelFunc),
	}

	}
	// allow overriding this value as well..
	if v := globalHealConfig.GetWorkers(); v > 0 {
		numHealers = uint64(v)
	}

	healingLogEvent(ctx, "Healing drive '%s' - use %d parallel workers.", tracker.disk.String(), numHealers)

	jt, _ := workers.New(int(numHealers))

	healEntryDone := func(name string) healEntryResult {
		return healEntryResult{
			entryDone: true,
			name:      name,
		}
	}

  };

  tensorflow::mutex execution_mutex_;
  ExecutionState execution_state_ TF_GUARDED_BY(execution_mutex_) =
      ExecutionState::kIdle;
  // Tells the worker thread that there is new work.
  tensorflow::condition_variable start_execute_;
  // The worker thread notifies that work has finished.
  tensorflow::condition_variable finished_execute_;
  // Notifies a StartExecute that the previous Join has finished.

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  protected void triggerShutdown() {}

  /**
   * Returns the {@link Executor} that will be used to run this service. Subclasses may override
   * this method to use a custom {@link Executor}, which may configure its worker thread with a
   * specific name, thread group or priority. The returned executor's {@link
   * Executor#execute(Runnable) execute()} method is called when this service is started, and should
   * return promptly.
   *

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        decides which workers to read from. If `"ANY"`, TF workers read from any
        tf.data service workers. If `"LOCAL"`, TF workers will only read from
        local in-processs tf.data service workers. `"AUTO"` works well for most
        cases, while users can specify other targets. For example, `"LOCAL"`
        would help avoid RPCs and data copy if every TF worker colocates with a