multimap.unfiltered().entries(),
        // explicit <Entry<K, V>> is required to build with JDK6
        Predicates.<Entry<K, V>>and(
            multimap.entryPredicate(), Maps.<V>valuePredicateOnEntries(Predicates.in(c))));
  }

  @Override
  public boolean retainAll(Collection<?> c) {
    return Iterables.removeIf(
        multimap.unfiltered().entries(),
        // explicit <Entry<K, V>> is required to build with JDK6

    /**
     * Gets the identifiers of those profiles that should be activated by explicit demand.
     *
     * @return The identifiers of those profiles to activate, never {@code null}.
     */
    List<String> getActiveProfileIds();

    /**
     * Sets the identifiers of those profiles that should be activated by explicit demand.
     *

  /**
   * Creates a new ArrayBasedCharEscaper instance with the given replacement map and specified safe
   * range. If {@code safeMax < safeMin} then no characters are considered safe. This initializer is
   * useful when explicit instances of ArrayBasedEscaperMap are used to allow the sharing of large
   * replacement mappings.
   *
   * <p>If a character has no mapped replacement then it is checked against the safe range. If it

    Optional<String> z = Optional.of("z");

    Comparator<Optional<String>> comparator = emptiesFirst(comparing(String::length));
    testComparator(comparator, empty, z, abc);

    // Just demonstrate that no explicit type parameter is required
    Comparator<Optional<String>> unused = emptiesFirst(naturalOrder());
  }

  public void testEmptiesLast() {
    Optional<String> empty = Optional.empty();

    @Override
    public List<String> getActiveProfileIds() {
        return activeProfileIds;
    }

    /**
     * Sets the identifiers of those profiles that should be activated by explicit demand.
     *
     * @param activeProfileIds The identifiers of those profiles to activate, may be {@code null}.
     * @return This context, never {@code null}.
     */

namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);
  ~GraphFunction() override;

  // GraphFunction maybe stay alive for the duration of the returned
  // FunctionDef.
  absl::Status GetFunctionDef(const FunctionDef** fdef) override;

// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };
  explicit AbstractFunction(AbstractFunctionKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.
  AbstractFunctionKind getKind() const { return kind_; }

#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Attributes of an op.
class AbstractOpAttrs {
 protected:
  enum AbstractOpAttrsKind { kEager, kTfrt };
  explicit AbstractOpAttrs(AbstractOpAttrsKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.
  AbstractOpAttrsKind getKind() const { return kind_; }
  virtual ~AbstractOpAttrs() = default;

    // Collapse equal elements, which Ordering.explicit() doesn't support, while
    // maintaining the ordering by first occurrence.
    Set<String> elementsPlus = Sets.newLinkedHashSet();
    elementsPlus.add(BEFORE_FIRST);
    elementsPlus.add(BEFORE_FIRST_2);
    elementsPlus.addAll(asList(elements));
    elementsPlus.add(AFTER_LAST);
    elementsPlus.add(AFTER_LAST_2);
    return Ordering.explicit(Lists.newArrayList(elementsPlus));
  }

  // The number of successful finished jobs to retain.
  // This is a pointer to distinguish between explicit zero and not specified.
  // Defaults to 3.
  // +optional
  optional int32 successfulJobsHistoryLimit = 6;

  // The number of failed finished jobs to retain.
  // This is a pointer to distinguish between explicit zero and not specified.
  // Defaults to 1.
  // +optional
  optional int32 failedJobsHistoryLimit = 7;