return delegate.add(object);
    }
    int[] entries = requireEntries();
    @Nullable Object[] elements = requireElements();

    int newEntryIndex = this.size; // current size, and pointer to the entry to be appended
    int newSize = newEntryIndex + 1;
    int hash = smearedHash(object);
    int mask = hashTableMask();
    int tableIndex = hash & mask;
    int next = CompactHashing.tableGet(requireTable(), tableIndex);

    }
    return tmp;
  }

  @Benchmark
  int log10(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += LongMath.log10(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int sqrt(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += LongMath.sqrt(positive[j], mode);
    }

  @Param({"100", "10000"})
  private int size;

  @Param private HeapType heap;

  private Queue<Integer> queue;

  private final Random random = new Random();

  @BeforeExperiment
  void setUp() {
    queue = heap.create(comparator.get());
    for (int i = 0; i < size; i++) {
      queue.add(random.nextInt());
    }
  }

  @Benchmark
  void pollAndAdd(int reps) {
    for (int i = 0; i < reps; i++) {

  static void checkAvalanche(HashFunction function, int trials, double epsilon) {
    Random rand = new Random(0);
    int keyBits = 32;
    int hashBits = function.bits();
    for (int i = 0; i < keyBits; i++) {
      int[] same = new int[hashBits];
      int[] diff = new int[hashBits];
      // go through trials to compute probability
      for (int j = 0; j < trials; j++) {
        int key1 = rand.nextInt();

        this.scope = scope;
    }

    public int getDepth() {
        return depth;
    }

    public void setDepth(int depth) {
        this.depth = depth;
    }

    public boolean isResolved() {
        return resolved;
    }

    public void setResolved(boolean resolved) {
        this.resolved = resolved;
    }

    public int getPomOrder() {
        return pomOrder;
    }

      for (int index : indexes) {
        builder.put(index, singleQuantileFromSorted(index, scale, dataset));
      }
      return builder.buildOrThrow();
    }

    private double singleQuantileFromSorted(int index, int scale, double[] dataset) {
      long numerator = (long) index * (dataset.length - 1);
      int positionFloor = (int) LongMath.divide(numerator, scale, RoundingMode.DOWN);

  private static byte[] toByteArray(int... bytes) {
    byte[] realBytes = new byte[bytes.length];
    for (int i = 0; i < bytes.length; i++) {
      realBytes[i] = (byte) bytes[i];
    }
    return realBytes;
  }

  private static void assertWellFormed(int... bytes) {
    assertTrue(Utf8.isWellFormed(toByteArray(bytes)));
  }

  private static void assertNotWellFormed(int... bytes) {

  @Override
  public final void add(int index, E element) {
    throw new UnsupportedOperationException();
  }

  @Override
  public final E remove(int index) {
    throw new UnsupportedOperationException();
  }

  @Override
  public UnmodifiableIterator<E> iterator() {
    return listIterator();
  }

  @Override
  public ImmutableList<E> subList(int fromIndex, int toIndex) {

This would be useful if you want to receive keys that you don't already know.

---

Another useful case is when you want to have keys of another type (e.g., `int`).

That's what we are going to see here.

In this case, you would accept any `dict` as long as it has `int` keys with `float` values:

{* ../../docs_src/body_nested_models/tutorial009_py39.py hl[7] *}

/// tip

---

Другой полезный случай — когда вы хотите, чтобы ключи были другого типа данных, например, `int`.

Именно это мы сейчас и увидим здесь.

В этом случае вы принимаете любой `dict`, пока у него есть ключи типа `int` со значениями типа `float`:

{* ../../docs_src/body_nested_models/tutorial009_py39.py hl[7] *}

/// tip | Совет