namespace tensorflow {

// Set the shapes and types of the output's handle.
//
// The lengths of the arrays pointed to by `shapes`, `ranks`, and `types` must
// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//
// TODO(akshayka): Implement a corresponding getter method.

        final ArtifactStatus that = (ArtifactStatus) o;

        return rank == that.rank;
    }

    @Override
    public int hashCode() {
        return rank;
    }

    @Override
    public String toString() {
        return key;
    }

    @Override
    public int compareTo(ArtifactStatus s) {
        return rank - s.rank;
    }

    this.rankMap = rankMap;
  }

  @Override
  public int compare(T left, T right) {
    return rank(left) - rank(right); // safe because both are nonnegative
  }

  private int rank(T value) {
    Integer rank = rankMap.get(value);
    if (rank == null) {
      throw new IncomparableValueException(value);
    }
    return rank;
  }

  @Override
  public boolean equals(@Nullable Object object) {

 */
package org.codelibs.fess.rank.fusion;

import java.util.Locale;

import org.codelibs.core.lang.StringUtil;
import org.codelibs.fess.entity.SearchRequestParams;
import org.codelibs.fess.mylasta.action.FessUserBean;
import org.dbflute.optional.OptionalThing;

/**
 * Abstract base class for rank fusion searchers in the Fess search system.
 * Rank fusion searchers are responsible for executing search queries and

	"http://dbflute.org/meta/lastadi10.dtd">
<components>
	<component name="rankFusionProcessor"
		class="org.codelibs.fess.rank.fusion.RankFusionProcessor">
		<postConstruct name="setSearcher">
			<arg>
				<component
					class="org.codelibs.fess.rank.fusion.DefaultSearcher">
				</component>
			</arg>
		</postConstruct>
	</component>

import org.codelibs.fess.util.ComponentUtil;
import org.opensearch.search.rescore.QueryRescorerBuilder;
import org.opensearch.search.rescore.RescorerBuilder;

/**
 * Learning to Rank query rescorer implementation.
 */
public class LtrQueryRescorer implements QueryRescorer {

    /**
     * Default constructor.
     */
    public LtrQueryRescorer() {
        // Default constructor
    }

  abstract Map<Integer, Double> multipleQuantiles(
      Collection<Integer> indexes, int scale, double[] dataset);

  static double getMinValue(double[] array, int from) {
    // This is basically a copy of com.google.math.Rank#getMinValue, with a small change in the
    // method signature: we always search to the end of the array.
    int min = from;
    for (int i = from + 1; i < array.length; i++) {
      if (array[min] > array[i]) {

import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryShardContext;

/**
 * A query builder for a stored LTR (Learning to Rank) query.
 * This builder constructs a query that uses a pre-trained LTR model
 * to re-rank search results based on a given set of features.
 */
public class StoredLtrQueryBuilder extends AbstractQueryBuilder<StoredLtrQueryBuilder> implements NamedWriteable {

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.rank.fusion;

import java.util.ArrayList;
import java.util.List;
import java.util.Map;

import org.apache.lucene.search.TotalHits.Relation;
import org.codelibs.fess.util.FacetResponse;

/**
 * Represents the result of a search operation in the rank fusion system.
 *
 * This class encapsulates all the information returned from a search query,