import org.opensearch.action.ActionRequest;
import org.opensearch.action.ActionType;
import org.opensearch.action.admin.cluster.health.ClusterHealthResponse;
import org.opensearch.action.admin.indices.segments.IndicesSegmentResponse;
import org.opensearch.action.admin.indices.segments.PitSegmentsRequest;
import org.opensearch.action.bulk.BulkRequest;
import org.opensearch.action.bulk.BulkRequestBuilder;
import org.opensearch.action.bulk.BulkResponse;

    CustomOpInfo new_node_info;
    switch (update_option) {
      case CustomOpUpdateOptions::kInputIndices: {
        const std::vector<std::string> indices =
            absl::StrSplit(node_specification, '-');
        for (const std::string& cur_index : indices) {
          custom_op_map[node_name].quantizable_input_indices.push_back(
              std::stoi(cur_index));
        }
        break;
      }

	res, err := c.Indices.ResolveIndex([]string{args.Index})
	if err != nil {
		return err
	}
	defer res.Body.Close()

	var v map[string]interface{}
	found := false
	if err := json.NewDecoder(res.Body).Decode(&v); err != nil {
		return fmt.Errorf("Error parsing response body: %v", err)
	}

	indices, ok := v["indices"].([]interface{})
	if ok {

  let description = [{
    Get a tensor in resource array.

    indices: the indices in the resource array.
    results: the tensor values for the corresponding indices.

    in_ch and out_ch are for control dependencies.
  }];

  let arguments = (ins
    TFRT_ChainType:$in_ch,
    StrAttr:$device,
    I64ArrayAttr:$indices
  );

  let results = (outs
    TFRT_ChainType:$out_ch,

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.suggest.analysis;

import java.util.List;

import org.opensearch.action.admin.indices.analyze.AnalyzeAction.AnalyzeToken;

public interface SuggestAnalyzer {
    List<AnalyzeToken> analyze(String text, String field, String lang);

//===----------------------------------------------------------------------===//

def LowerTensorScatterAdd: Pat<
  (TF_TensorScatterAddOp $input, $indices, $updates),
  (TF_TensorScatterUpdateOp $input, $indices,
     (TF_AddOp $updates, (CreateGatherNdOp $updates, $input, $indices)))>;

//===----------------------------------------------------------------------===//
// AddV2 op patterns.

  (replaceWithValue $params),
  [(CanOptimizeIdentityGatherNdOrScatterNdOp $params, $indices, $output)]>;

def OptimizeIdentityScatterNdOp : Pat<
  (TFL_ScatterNdOp:$output (Arith_ConstantOp I32ElementsAttr: $indices), $params, $ignored),
  (replaceWithValue $params),
  [(CanOptimizeIdentityGatherNdOrScatterNdOp $params, $indices, $output)]>;

    }
  }

  return indices;
}

// Given a list of tensor indices, returns true if any of the tensors have
// non-empty name strings.
bool HasNonEmptyNames(const tflite::SubGraphT& subgraph,
                      ArrayRef<int32_t> indices) {
  return llvm::any_of(
      indices, [&](int i) { return !subgraph.tensors.at(i)->name.empty(); });
}

    // final_op = "Div"
    llvm::SmallVector<int64_t> indices(group_size.getInt());
    std::iota(indices.begin(), indices.end(), 0);

    auto replica_groups = mlir::DenseIntElementsAttr::get(
        mlir::RankedTensorType::get({1, group_size.getInt()},
                                    rewriter.getI64Type()),
        indices);

    {

      op->setAttr(attr.getName(),
                  FlatSymbolRefAttr::get(op->getContext(), cloned.getName()));
      break;
    }
  }

  // Traverse results backward so that indices to be deleted stay unchanged.
  for (OpResult result : llvm::reverse(op->getResults())) {
    if (!result.use_empty()) continue;
    int result_idx = result.getResultNumber();
    for (func::FuncOp func : cloned_branches)