const auto& shape = reader->GetVariableToShapeMap().at(name);
  int rank = shape.dims();
  if (num_dims != rank) {
    status->status = InvalidArgument("Expected rank is ", num_dims,
                                     " but actual rank is ", rank);
    return;
  }
  for (int i = 0; i < num_dims; i++) {
    dims[i] = shape.dim_size(i);
  }
}

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.rank.fusion;

import java.util.HashMap;
import java.util.Map;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.core.collection.ArrayUtil;

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,

    final T value;
    final int rank;

    Composite(T value, int rank) {
      this.value = value;
      this.rank = rank;
    }

    // natural order is by rank only; the test will compound() this with the
    // order of 't'.
    @Override
    public int compareTo(Composite<T> that) {
      return Integer.compare(rank, that.rank);
    }

    final T value;
    final int rank;

    Composite(T value, int rank) {
      this.value = value;
      this.rank = rank;
    }

    // natural order is by rank only; the test will compound() this with the
    // order of 't'.
    @Override
    public int compareTo(Composite<T> that) {
      return Integer.compare(rank, that.rank);
    }

  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  int rank = -1;
  if (ic->RankKnown(shape)) {
    rank = ic->Rank(shape);
  }

  if (num_dims != rank) {
    status->status = InvalidArgument("Expected rank is ", num_dims,
                                     " but actual rank is ", rank);
    return;
  }

  if (num_dims == 0) {
    // Output shape is a scalar.

labels.facet_filetype_txt=filetype:txt\t\
labels.facet_filetype_others=filetype:others\n\

# ranking

# Window size for rank fusion.
rank.fusion.window_size=200
# Rank constant for rank fusion.
rank.fusion.rank_constant=20
# Number of threads for rank fusion.
rank.fusion.threads=-1
# Score field for rank fusion.
rank.fusion.score_field=rf_score

# acl

# Whether to get SMB roles from a file.
smb.role.from.file=true

     */
    public static CorsHandlerFactory getCorsHandlerFactory() {
        return getComponent(CORS_HANDLER_FACTORY);
    }

    /**
     * Gets the rank fusion processor component.
     * @return The rank fusion processor.
     */
    public static RankFusionProcessor getRankFusionProcessor() {
        return getComponent(RANK_FUSION_PROCESSOR);
    }

    /**

// 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.