@Benchmark
  int hashMultiset(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Object value : hashMultiset) {
        sum += value.hashCode();
      }
    }
    return sum;
  }

  @Benchmark
  int linkedHashMultiset(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Object value : linkedHashMultiset) {
        sum += value.hashCode();
      }
    }

		unsealConfig = sio.Config{MinVersion: sio.Version20, Key: mac.Sum(nil), CipherSuites: fips.DARECiphers()}
	case InsecureSealAlgorithm:
		sha := sha256.New()
		sha.Write(extKey)
		sha.Write(sealedKey.IV[:])
		unsealConfig = sio.Config{MinVersion: sio.Version10, Key: sha.Sum(nil), CipherSuites: fips.DARECiphers()}
	}

    powerSet = Sets.powerSet(set);
  }

  @Benchmark
  int iteration(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Set<Integer> subset : powerSet) {
        for (Integer value : subset) {
          sum += value;
        }
      }
    }
    return sum;
  }

		}
		var (
			hash = algorithm.New()
			msg  = make([]byte, 0, hash.Size()*hash.BlockSize())
			sum  = make([]byte, 0, hash.Size())
		)
		for i := 0; i < hash.Size()*hash.BlockSize(); i += hash.Size() {
			hash.Write(msg)
			sum = hash.Sum(sum[:0])
			msg = append(msg, sum...)
			hash.Reset()
		}
		if !bytes.Equal(sum, checksum) {

            opLambda.callback(builder);
        }
    }

    public void setAvailable_Sum() {
        setAvailable_Sum(null);
    }

    public void setAvailable_Sum(ConditionOptionCall<SumAggregationBuilder> opLambda) {
        setAvailable_Sum("available", opLambda);
    }

    public void setAvailable_Sum(String name, ConditionOptionCall<SumAggregationBuilder> opLambda) {

				return 0, SizeTooLarge{Want: r.expectedMax, Got: r.bytesRead}
			}
		}

		if r.sha256 != nil {
			if sum := r.sha256.Sum(nil); !bytes.Equal(r.contentSHA256, sum) {
				return n, SHA256Mismatch{
					ExpectedSHA256:   hex.EncodeToString(r.contentSHA256),
					CalculatedSHA256: hex.EncodeToString(sum),
				}
			}
		}
		if r.contentHasher != nil {
			if r.contentHash.Type.Trailing() {
				var err error

        double sum = 0.0;
        for (double value : values) {
          sum += value;
        }
        return sum / values.length;
      }
    },
    KAHAN {
      @Override
      double mean(double[] values) {
        double sum = 0.0;
        double c = 0.0;
        for (double value : values) {
          double y = value - c;
          double t = sum + y;
          c = (t - sum) - y;

      return new CacheStats(
          negativeToMaxValue(hitCount.sum()),
          negativeToMaxValue(missCount.sum()),
          negativeToMaxValue(loadSuccessCount.sum()),
          negativeToMaxValue(loadExceptionCount.sum()),
          negativeToMaxValue(totalLoadTime.sum()),
          negativeToMaxValue(evictionCount.sum()));
    }

        "name": "workload",
        "options": [],

        ctx, vals.data(), vals_shape, 1, &sum_dims_raw));
    sum_dims.reset(sum_dims_raw);
  }

  // Reduce sum the output on all dimensions.
  TF_RETURN_IF_ERROR(ops::Sum(ctx, model_out.get(), sum_dims.get(), &outputs[0],
                              /*keep_dims=*/false, "sum_output"));
  return absl::OkStatus();
}
// ========================= End Helper Functions==============================