indices, err := c.allocate(ctx, model)
	return len(indices) == len(c.requests), err
}

func (c *Controller) Allocate(ctx context.Context, model Model) ([]*resourceapi.NamedResourcesAllocationResult, error) {
	indices, err := c.allocate(ctx, model)
	if err != nil {
		return nil, err
	}
	if len(indices) != len(c.requests) {
		return nil, errors.New("insufficient resources")

	case *ast.IndexExpr:
		return &IndexExpr{
			Orig:    e,
			X:       e.X,
			Lbrack:  e.Lbrack,
			Indices: []ast.Expr{e.Index},
			Rbrack:  e.Rbrack,
		}
	case *ast.IndexListExpr:
		return &IndexExpr{
			Orig:    e,
			X:       e.X,
			Lbrack:  e.Lbrack,
			Indices: e.Indices,
			Rbrack:  e.Rbrack,
		}
	}
	return nil

		// indices in the first place (if it returned fewer than that then
		// there cannot be more).
		for n1 := n; ; n1 += 2 * (n - len(result)) /* overflow ok */ {
			indices := x.Lookup(lit, n1)
			if len(indices) == 0 {
				return
			}
			slices.Sort(indices)
			pairs := make([]int, 2*len(indices))
			result = make([][]int, len(indices))
			count := 0
			prev := 0

		return e.X, e.Lbrack, e.Indices, e.Rbrack
	}
	return nil, token.NoPos, nil, token.NoPos
}

// PackIndexExpr returns an *ast.IndexExpr or *ast.IndexListExpr, depending on
// the cardinality of indices. Calling PackIndexExpr with len(indices) == 0
// will panic.
func PackIndexExpr(x ast.Expr, lbrack token.Pos, indices []ast.Expr, rbrack token.Pos) ast.Expr {
	switch len(indices) {
	case 0:
		panic("empty indices")

import org.opensearch.action.admin.indices.exists.indices.IndicesExistsResponse;
import org.opensearch.action.admin.indices.mapping.get.GetFieldMappingsResponse;
import org.opensearch.action.admin.indices.mapping.get.GetFieldMappingsResponse.FieldMappingMetadata;
import org.opensearch.action.admin.indices.mapping.get.GetMappingsResponse;
import org.opensearch.action.admin.indices.mapping.put.PutMappingRequestBuilder;

namespace {

// Returns contiguous offset (address) of the position represented by `indices`
// in a `shape` shaped tensor. Assumes row-major order. `indices` and `shape`
// should have the same size.
// Example: Index (2, 3) of a (4, 5)-shaped tensor has the contiguous offset of
// 2 * 5 + 3 = 13.
int64_t GetContiguousOffset(const ArrayRef<int64_t> indices,
                            const ArrayRef<int64_t> shape) {

     *
     * @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;

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>)