* specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.plugin.lifecycle;

/**
 * A set of goals to execute.
 *
 * @version $Revision$ $Date$
 */
@SuppressWarnings("all")
public class Execution implements java.io.Serializable {

    // --------------------------/
    // - Class/Member Variables -/
    // --------------------------/

    /**

   * calls to {@link Executor#execute execute()} that submitted those tasks had.
   *
   * <p>The executor uses {@code delegate} in order to {@link Executor#execute execute} each task in
   * turn, and does not create any threads of its own.
   *
   * <p>After execution begins on a thread from the {@code delegate} {@link Executor}, tasks are

  /**
   * Returns a {@link ScheduledExecutorService} that never executes anything.
   *
   * <p>The {@code shutdownNow} method of the returned executor always returns an empty list despite
   * the fact that everything is still technically awaiting execution. The {@code getDelay} method
   * of any {@link ScheduledFuture} returned by the executor will always return the max long value
   * instead of the time until the user-specified delay.

    } else {
      for (i in 0 until executableCalls.size) {
        val asyncCall = executableCalls[i]
        asyncCall.executeOn(executorService)
      }
    }

    return isRunning
  }

  /** Used by [Call.execute] to signal it is in-flight. */
  internal fun executed(call: RealCall) =
    this.withLock {
      runningSyncCalls.add(call)
    }

      final Runnable runnable;
      final Executor executor;

      RunnableExecutorPair(Runnable runnable, Executor executor) {
        this.runnable = runnable;
        this.executor = executor;
      }

      void execute() {
        try {
          executor.execute(runnable);
        } catch (RuntimeException e) {
          log.log(
              Level.SEVERE,
              "RuntimeException while executing runnable "

which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.

      /** The future that represents the next execution of this task. */
      @GuardedBy("lock")
      @CheckForNull
      private SupplantableFuture cancellationDelegate;

      ReschedulableCallable(
          AbstractService service, ScheduledExecutorService executor, Runnable runnable) {
        this.wrappedRunnable = runnable;
        this.executor = executor;
        this.service = service;
      }

<plugins>
  <plugin>
    <groupId>org.apache.maven.plugins</groupId>
    <artifactId>maven-resources-plugin</artifactId>
    <executions>
      <execution>
        <goals>
          <goal>process</goal>
        </goals>
      </execution>
    </executions>
  </plugin>
  .
  .
  .
</plugins>

        <plugin>
          <groupId>build</groupId>
          <artifactId>managed-plugin</artifactId>
          <executions>
            <execution>
              <phase>test</phase>
            </execution>
            <execution>
              <phase>test</phase>
            </execution>
          </executions>
        </plugin>
      </plugins>
    </pluginManagement>
    <plugins>
      <plugin>

    executor.execute(task);
    return task;
  }

  /**
   * Executes {@code runnable} on the specified {@code executor}, returning a {@code Future} that
   * will complete after execution.
   *
   * @throws RejectedExecutionException if the task cannot be scheduled for execution
   * @since 28.2
   */
  public static ListenableFuture<@Nullable Void> submit(Runnable runnable, Executor executor) {