Klaus Post <******@****.***> 1729611050 -0700

Istio Automation <******@****.***> 1730874205 -0500

  @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();
      }
    }

  @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();
      }
    }

  }

  public void testSum() {
    assertThat(EMPTY_STATS_VARARGS.sum()).isEqualTo(0.0);
    assertThat(EMPTY_STATS_ITERABLE.sum()).isEqualTo(0.0);
    assertThat(ONE_VALUE_STATS.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(TWO_VALUES_STATS.sum()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN * 2);
    assertThat(MANY_VALUES_STATS_VARARGS.sum())
        .isWithin(ALLOWED_ERROR)

      }
    }
  }

  /** getAndAccumulate with sum adds given value to current, and returns previous value */
  public void testGetAndAccumulateWithSum() {
    for (double x : VALUES) {
      for (double y : VALUES) {
        AtomicDouble a = new AtomicDouble(x);
        double z = a.getAndAccumulate(y, Double::sum);
        assertBitEquals(x, z);
        assertBitEquals(x + y, a.get());
      }

  }

  public void testSum() {
    assertThat(emptyAccumulator.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyIterable.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyStats.sum()).isEqualTo(0.0);
    assertThat(oneValueAccumulator.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(oneValueAccumulatorByAddAllEmptyStats.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);

        for (int i = 0; i < elements.length; i++) {
          // add to either; sum should contain all
          if (i % 2 == 0) {
            multiset1.add(elements[i]);
          } else {
            multiset2.add(elements[i]);
          }
        }
        return sum(multiset1, multiset2);
      }
    };
  }

  private static TestStringMultisetGenerator differenceGenerator() {

  // If the output is a scalar, then return the scalar output
  if (num_dims_out == 0) {
    outputs[0] = model_out.release();
    return absl::OkStatus();
  }

  // Else, reduce sum the output to get a scalar

  // Will sum all dimensions, so get a Tensor containing [0,...,num_dims_out-1].
  AbstractTensorHandlePtr sum_dims;
  {
    vector<int32_t> vals(num_dims_out);
    int64_t vals_shape[] = {num_dims_out};

  }

  public void testSum() {
    assertThat(emptyAccumulator.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyIterable.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyStats.sum()).isEqualTo(0.0);
    assertThat(oneValueAccumulator.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(oneValueAccumulatorByAddAllEmptyStats.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);