}

  private TypeToken<? super T> getSupertypeFromUpperBounds(
      Class<? super T> supertype, Type[] upperBounds) {
    for (Type upperBound : upperBounds) {
      @SuppressWarnings("unchecked") // T's upperbound is <? super T>.
      TypeToken<? super T> bound = (TypeToken<? super T>) of(upperBound);
      if (bound.isSubtypeOf(supertype)) {

                    return typeParameterDescriptor.upperBounds.flatMap { getUpperBounds(it) }
                }

                val typeConstructor = type.constructor
                if (typeConstructor is NewTypeVariableConstructor) {
                    return typeConstructor.originalTypeParameter?.upperBounds.orEmpty().flatMap { getUpperBounds(it) }
                }

  }

  private TypeToken<? super T> getSupertypeFromUpperBounds(
      Class<? super T> supertype, Type[] upperBounds) {
    for (Type upperBound : upperBounds) {
      @SuppressWarnings("unchecked") // T's upperbound is <? super T>.
      TypeToken<? super T> bound = (TypeToken<? super T>) of(upperBound);
      if (bound.isSubtypeOf(supertype)) {

    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

        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);

		plNames = append(plNames, plName)
		items = append(items, allocProblemItem{
			lowerBound: minCurrentCL,
			upperBound: float64(plState.maxCL),
			target:     math.Max(minCurrentCL, plState.seatDemandStats.smoothed),
		})
	}
	if len(items) == 0 && cfgCtlr.nominalCLSum > 0 {

      "UniformQuantizedAdd",
      "UniformQuantizedClipByValue",
      "UniformQuantizedConvolution",
      "UniformQuantizedDot",
      "UniformRequantize",
      "Unique",
      "UniqueV2",
      "UpperBound",
      "UnsortedSegmentMax",
      "UnsortedSegmentMin",
      "UnsortedSegmentProd",
      "UnsortedSegmentSum",
      "VarIsInitializedOp",
      "VariableShape",
      "Where",
      "While",

*   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)
		}