* <p>As an example, imagine that we have a list of tasks to execute, but we don't want to submit
 * more than 2 per second:
 *
 * <pre>{@code
 * final RateLimiter rateLimiter = RateLimiter.create(2.0); // rate is "2 permits per second"
 * void submitTasks(List<Runnable> tasks, Executor executor) {
 *   for (Runnable task : tasks) {
 *     rateLimiter.acquire(); // may wait
 *     executor.execute(task);
 *   }
 * }
 * }</pre>
 *

  //
  // Example: If one calls `op->SetDeviceName("/device:GPU")`, the value
  // returned by DeviceName should be "/device:GPU:*" until a particular GPU is
  // chosen for the operation by the device placement logic in the
  // executor. After that, the value returned by DeviceName will be a full
  // device name such as "/job:localhost/replica:0/task:0/device:GPU:1".
  virtual const string& DeviceName() const = 0;

  // Sets the operation device name.
  //

        // If the context's default exector is set to async, re-using that in
        // each thread would cause collectives to deadlock. For consistency we
        // create a new sync executor for every thread.
        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.
        device_(device),
        executor_(

labels.pos=POS
labels.purgeJobLogDay=Purge Job Log Before
labels.purgeUserInfoDay=Purge User Before
labels.reading=Reading
labels.roleTypeIds=Role ID
labels.scriptData=Script
labels.scriptResult=Result
labels.scriptType=Executor
labels.segmentation=Segmentation
labels.startTime=Start Time
labels.target=Target
labels.token=Token
labels.synonymFile=Synonym File
labels.stopwordsFile=Stopwords File

  parallel_device.Execute(context.get(), handle_inputs, "ReadVariableOp",
                          TFE_OpGetAttrs(read_op.get()),
                          /*expected_max_outputs=*/1, status.get());
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);
  TF_SetStatus(status.get(), TF_OK, "");

  // Check that ops still run successfully on the device.
  parallel_device.Execute(context.get(), std::vector<ParallelTensor*>(),

labels.purgeJobLogDay=Bereinige Suchprotokoll nach
labels.purgeUserInfoDay=Bereinige Benutzer nach
labels.reading=Lesen
labels.roleTypeIds=Rollen-ID
labels.scriptData=Skript
labels.scriptResult=Suchergebnis
labels.scriptType=Executor
labels.segmentation=Segmentierung
labels.startTime=Startzeitpunkt
labels.target=Ziel
labels.token=Token
labels.synonymFile=Datei mit Synonymen
labels.elevateWordFile=Datei mit zusätzlichen Wörtern

Sometimes there's an action required like calling the application layer or responding to a ping, and the thread discovering the action is not the thread that should do the work. We enqueue a runnable on this executor and it gets handled by one of the executor's threads.

### Locks

We have 3 different things that we synchronize on.

#### Http2Connection

              </models>
            </configuration>
          </execution>
        </executions>
      </plugin>
      <plugin>
        <groupId>org.codehaus.mojo</groupId>
        <artifactId>buildnumber-maven-plugin</artifactId>
        <executions>
          <execution>
            <id>create-buildnumber</id>
            <goals>
              <goal>create</goal>

labels.scheduledjob_target	=	Cible
labels.scheduledjob_status	=	État
labels.scheduledjob_cronExpression	=	Tableau
labels.scheduledjob_scriptType	=	Executor
labels.scheduledjob_scriptData	=	Script
labels.scheduledjob_jobLogging	=	Logging
labels.scheduledjob_crawler	=	Tâche d'exploration
labels.scheduledjob_running	=	Éxecuter
labels.scheduledjob_active	=	Actif
labels.scheduledjob_nojob	=	Inactif
labels.scheduledjob_button_start	=	Commencez maintenant.

labels.scheduledjob_title_details=Jobs
labels.scheduledjob_name=Name
labels.scheduledjob_target=Target
labels.scheduledjob_status=Status
labels.scheduledjob_cronExpression=Schedule
labels.scheduledjob_scriptType=Executor
labels.scheduledjob_scriptData=Script
labels.scheduledjob_jobLogging=Logging
labels.scheduledjob_crawler=Crawler Job
labels.scheduledjob_running=Running
labels.scheduledjob_active=Active