given:
        def gradleVersion = GradleVersion.version("9.2")
        def allVersions = [
            "8.8.0", "8.9.0",
            "9.0.0-alpha01", "9.0.0-beta01", "9.0.0-rc01"
        ].shuffled()

        when:
        def selected = UpdateAgpVersions.selectVersionsFrom(gradleVersion, null, allVersions)

        then:
        selected == ["8.9.0", "9.0.0-rc01"]
    }

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.
    * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using  `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).

*   `tf.math`

            }
            return true;
        });
    }
    window.addEventListener("scroll", loadVisibleTermynals);
    createTermynals();
    loadVisibleTermynals();
}

function shuffle(array) {
    var currentIndex = array.length, temporaryValue, randomIndex;
    while (0 !== currentIndex) {
        randomIndex = Math.floor(Math.random() * currentIndex);
        currentIndex -= 1;

  private final boolean allowNulls;

  // Package-private so that it can be extended.
  MinimalCollection(Class<? super @NonNull E> type, boolean allowNulls, E... contents) {
    // TODO: consider making it shuffle the contents to test iteration order.
    this.contents = Platform.clone(contents);
    this.type = type;
    this.allowNulls = allowNulls;

    if (!allowNulls) {
      for (Object element : contents) {

  private final boolean allowNulls;

  // Package-private so that it can be extended.
  MinimalCollection(Class<? super @NonNull E> type, boolean allowNulls, E... contents) {
    // TODO: consider making it shuffle the contents to test iteration order.
    this.contents = Platform.clone(contents);
    this.type = type;
    this.allowNulls = allowNulls;

    if (!allowNulls) {
      for (Object element : contents) {

    for (int i = 0; i < 10; i++) {
      hashCodes.add(HashCode.fromLong(random.nextLong()));
    }
    HashCode hashCode1 = Hashing.combineOrdered(hashCodes);
    Collections.shuffle(hashCodes, random);
    HashCode hashCode2 = Hashing.combineOrdered(hashCodes);

    assertFalse(hashCode1.equals(hashCode2));
  }

  public void testCombineUnordered_empty() {
    assertThrows(

            return null;
          });
    }
    assertEquals(allTasks.size() + 1, barrier.getParties());
    for (int i = 0; i < 1000; i++) {
      Collections.shuffle(allTasks);
      AbstractFuture<String> future = new AbstractFuture<String>() {};
      currentFuture.set(future);
      for (Callable<?> task : allTasks) {

    for (int attempts = 0; attempts < reduceIterationsIfGwt(1000); attempts++) {
      ArrayList<Integer> elements = createOrderedList(10);
      shuffle(elements, random);
      MinMaxPriorityQueue<Integer> queue = MinMaxPriorityQueue.create(elements);
      shuffle(elements, random);
      for (Integer element : elements) {
        assertThat(queue.remove(element)).isTrue();
        assertIntact(queue);

    for (int attempts = 0; attempts < reduceIterationsIfGwt(1000); attempts++) {
      ArrayList<Integer> elements = createOrderedList(10);
      shuffle(elements, random);
      MinMaxPriorityQueue<Integer> queue = MinMaxPriorityQueue.create(elements);
      shuffle(elements, random);
      for (Integer element : elements) {
        assertThat(queue.remove(element)).isTrue();
        assertIntact(queue);

      indexes.add(index);
      expectedBuilder.put(index, expectedLargeDatasetPercentile(index));
    }
    Random random = new Random(770683168895677741L);
    Collections.shuffle(indexes, random);
    assertThat(percentiles().indexes(Ints.toArray(indexes)).compute(PSEUDORANDOM_DATASET))
        .comparingValuesUsing(QUANTILE_CORRESPONDENCE)
        .containsExactlyEntriesIn(expectedBuilder.buildOrThrow());