// it.
    executeListener(runnable, executor);
  }

  /**
   * Runs this execution list, executing all existing pairs in the order they were added. However,
   * note that listeners added after this point may be executed before those previously added, and
   * note that the execution order of all listeners is ultimately chosen by the implementations of
   * the supplied executors.
   *

import org.apache.maven.artifact.repository.ArtifactRepository;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.execution.DefaultMavenExecutionRequest;
import org.apache.maven.execution.DefaultMavenExecutionResult;
import org.apache.maven.execution.MavenExecutionRequest;
import org.apache.maven.execution.MavenSession;
import org.apache.maven.impl.InternalSession;
import org.apache.maven.internal.impl.DefaultLookup;

          </params>
        </configuration>
        <executions>
          <execution>
            <id>modello</id>
            <goals>
              <goal>velocity</goal>
              <goal>xdoc</goal>
              <goal>xsd</goal>
            </goals>
            <phase>generate-resources</phase>
          </execution>
        </executions>
      </plugin>
      <plugin>

          </params>
        </configuration>
        <executions>
          <execution>
            <id>modello</id>
            <goals>
              <goal>velocity</goal>
              <goal>xdoc</goal>
              <goal>xsd</goal>
            </goals>
            <phase>generate-resources</phase>
          </execution>
        </executions>
      </plugin>
      <plugin>

        </configuration>
        <executions>
          <execution>
            <id>modello</id>
            <goals>
              <goal>velocity</goal>
              <goal>xdoc</goal>
              <goal>xsd</goal>
            </goals>
            <phase>generate-sources</phase>
          </execution>
        </executions>
      </plugin>
    </plugins>
  </build>

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.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

        scoreUpdater.addScoreBooster(booster2);
        scoreUpdater.addScoreBooster(booster3);

        // Clear execution order before test
        PriorityTrackingBooster.clearExecutionOrder();

        scoreUpdater.execute();

        // Due to integer overflow in comparator, execution order is affected for extreme values
        // The comparator b2 - b1 with MAX_VALUE and MIN_VALUE causes overflow

			</plugin>
			<plugin>
				<groupId>com.github.hazendaz.maven</groupId>
				<artifactId>yuicompressor-maven-plugin</artifactId>
				<executions>
					<execution>
						<phase>compile</phase>
						<goals>
							<goal>compress</goal>
						</goals>
					</execution>
				</executions>
				<configuration>
					<nosuffix>true</nosuffix>

    // it.
    executeListener(runnable, executor);
  }

  /**
   * Runs this execution list, executing all existing pairs in the order they were added. However,
   * note that listeners added after this point may be executed before those previously added, and
   * note that the execution order of all listeners is ultimately chosen by the implementations of
   * the supplied executors.
   *

import static java.lang.annotation.ElementType.TYPE;
import static java.lang.annotation.RetentionPolicy.RUNTIME;

/**
 * Indicates that annotated component should be instantiated before session execution starts
 * and discarded after session execution completes.
 * <p>
 * A {@code org.apache.maven.api.Session} object is available in the scope of this annotation.
 *
 * @since 4.0.0
 */
@Scope
@Documented
@Retention(RUNTIME)