return Multisets.iteratorImpl(this);
  }

  @Override
  public SortedMultiset<E> headMultiset(@ParametricNullness E upperBound, BoundType boundType) {
    return new TreeMultiset<>(
        rootReference,
        range.intersect(GeneralRange.upTo(comparator(), upperBound, boundType)),
        header);
  }

  @Override

    return Multisets.iteratorImpl(this);
  }

  @Override
  public SortedMultiset<E> headMultiset(@ParametricNullness E upperBound, BoundType boundType) {
    return new TreeMultiset<>(
        rootReference,
        range.intersect(GeneralRange.upTo(comparator(), upperBound, boundType)),
        header);
  }

  @Override

    Cut<Integer> c = Range.greaterThan(0).lowerBound;
    Cut<Integer> d = Range.atLeast(1).lowerBound;
    Cut<Integer> e = Range.greaterThan(1).lowerBound;
    Cut<Integer> f = Range.greaterThan(1).upperBound;

    testCompareToAndEquals(ImmutableList.of(a, b, c, d, e, f));
  }

  @SuppressWarnings("DistinctVarargsChecker")
  public void testContainsAll() {
    Range<Integer> range = Range.closed(3, 5);

        NavigableMap<Cut<Integer>, Range<Integer>> expectedRangesByUpperBound = Maps.newTreeMap();
        for (Range<Integer> range : rangeSet.asRanges()) {
          expectedRangesByUpperBound.put(range.upperBound, range);
        }
        testNavigationAgainstExpected(
            expectedRangesByUpperBound,
            new TreeRangeSet.RangesByUpperBound<Integer>(rangeSet.rangesByLowerBound),
            CUTS_TO_TEST);

*   Remove the `tf.keras.dtensor.experimental.layout_map_scope()`. You can user the `tf.keras.dtensor.experimental.LayoutMap.scope()` instead.

## Security

*   Fixes correct values rank in UpperBound and LowerBound [CVE-2023-33976](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2023-33976)

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as:

				if *lp.Name == "api" && toLowerAPILabels {
					labels[*lp.Name] = strings.ToLower(*lp.Value)
				} else {
					labels[*lp.Name] = *lp.Value
				}
			}
			labels["le"] = fmt.Sprintf("%.3f", *b.UpperBound)
			metric := MetricV2{
				Description:    desc,
				VariableLabels: labels,
				Value:          float64(b.GetCumulativeCount()),
			}
			metrics = append(metrics, metric)
		}