func.func @main() -> (!tf_mlrt.tensor, !tf_mlrt.tensor) {
  // CHECK-NEXT: [[r:%.*]]:3 = tf_mlrt.get_resource {indices = [2, 0, 1]}
  // CHECK-NEXT: [[v:%.*]] = tf_mlrt.executeop([[r]]#0, [[r]]#1)
  // CHECK-NEXT: return [[v]], [[r]]#2
  %0 = tf_mlrt.get_resource {indices = [2]} : !tf_mlrt.tensor
  %1 = tf_mlrt.get_resource {indices = [0]} : !tf_mlrt.tensor

     *
     * @param target the target location
     * @param source the source location
     * @param indices the list of integers for the indices
     * @return the merged location
     */
    public static InputLocation merge(InputLocation target, InputLocation source, Collection<Integer> indices) {
        if (source == null) {
            return target;

import java.util.List;

import org.codelibs.fess.suggest.settings.AnalyzerSettings;
import org.codelibs.fess.suggest.settings.SuggestSettings;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction.AnalyzeToken;
import org.opensearch.client.Client;

public class AnalyzerNormalizer implements Normalizer {
    protected final Client client;

public final class ProjectIndex {

    private final Map<String, MavenProject> projects;

    private final Map<String, Integer> indices;

    public ProjectIndex(List<MavenProject> projects) {
        this.projects = new HashMap<>(projects.size() * 2);
        this.indices = new HashMap<>(projects.size() * 2);

        for (int i = 0; i < projects.size(); i++) {
            MavenProject project = projects.get(i);

import java.util.List;

import org.codelibs.fess.suggest.settings.AnalyzerSettings;
import org.codelibs.fess.suggest.settings.SuggestSettings;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction.AnalyzeToken;
import org.opensearch.client.Client;
import org.opensearch.core.common.Strings;

import com.ibm.icu.text.Transliterator;

// CHECK-NEXT: tfrt.return [[out_chain]], [[res]] : !tfrt.chain, !tfrt_fallback.tf_tensor
func.func @gather(%indices: tensor<?xi32>,
             %resource: tensor<*x!tf_type.resource>) -> tensor<*xi32> {
  %0 = "tf.ResourceGather"(%resource, %indices) {batch_dims = 0 : i64, device = "/device:CPU:0", validate_indices = true}: (tensor<*x!tf_type.resource>, tensor<?xi32>) -> (tensor<*xi32>)

  // CHECK-NOT: tf.HashTableV2
  // CHECK-NOT: tf.LookupTableSizeV2
  // CHECK-DAG: [[v0:%.*]] = "tf._TfrtGetResource"() <{container = [""], indices = [[[handle_id]]], shared_name = [{{.*}}]}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"}
  // CHECK-DAG: [[v1:%.*]] = "tf._TfrtGetResource"() <{container = [""], indices = [[[size_id]]], shared_name = [{{.*}}]}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"}

// Gathers elements in buffer with the indices.
Value GatherElements(Value indices, Value buffer, OpBuilder builder,
                     Location loc);

// Scatters elements into buffer, where each scattered element is accumulated
// with the old value in buffer.
Value ScatterAccumulateElements(Value indices, Value updates, Value buffer,

    }
  }
  return resource_vec;
}

LogicalResult _TfrtGetResourceOp::verify() {
  _TfrtGetResourceOp get_resource_op = *this;
  // The sizes of indices, shared_name and container must be equal.
  int32_t indices_size =
      get_resource_op->getAttrOfType<mlir::ArrayAttr>("indices").size();
  int32_t shared_name_size =
      get_resource_op->getAttrOfType<mlir::ArrayAttr>("shared_name").size();
  int32_t container_size =

      /*methodBody=*/[{
        return $_op.getDataFormat();
    }]>,
    InterfaceMethod<
      [{Returns indices of layout dependent arguments.}],
      "SmallVector<unsigned, 4>", "GetLayoutDependentArgs", (ins)
    >,
    InterfaceMethod<
      [{Returns indices of layout dependent results.}],
      "SmallVector<unsigned, 4>", "GetLayoutDependentResults", (ins)
    >,
    InterfaceMethod<