return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {
        return randomNonNegativeBigInteger(numBits);
      }

 *
 * @author mike nonemacher
 */

@NullUnmarked
public class PopulatedCachesTest extends TestCase {
  // we use integers as keys; make sure the range covers some values that ARE cached by
  // Integer.valueOf(int), and some that are not cached. (127 is the highest cached value.)
  static final int WARMUP_MIN = 120;
  static final int WARMUP_MAX = 135;

 * George: [Washington, Bush, Bush]
 * Grover: [Cleveland, Cleveland]        // Two, non-consecutive terms, rep'ing NJ!
 * ...
 * }
 *
 * <h3>Views</h3>
 *
 * <p>Much of the power of the multimap API comes from the <i>view collections</i> it provides.
 * These always reflect the latest state of the multimap itself. When they support modification, the

		t.Fatalf("count lang: %v", err)
	}
	if count != 1 {
		t.Fatalf("expected language row still exists, got %d", count)
	}
}

// Multi-owners: HasMany update and delete
func TestClauseAssociationSetUpdateAndDeleteManyOwnersHasMany(t *testing.T) {
	ctx := context.Background()
	u1 := User{Name: "MultiOwners-HasMany-1", Age: 21}
	u1.Pets = []*Pet{{Name: "p1"}}

        verify(treeConnection).getConnectedShare();
    }

    @Test
    @DisplayName("isSameTree: different types and delegated compare")
    void isSameTreeCoversBranches() {
        // Covers non-impl (false) and impl path delegating to connection comparison
        // Not an impl -> false
        assertFalse(handle.isSameTree(mock(SmbTreeHandle.class)));

        // Impl case delegates to treeConnection.isSame

[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
[community](https://www.tensorflow.org/community) resources that lets
researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine

  // are replaced by a single `elements` array but everything else works similarly.

  /**
   * The hashtable object. This can be either:
   *
   * <ul>
   *   <li>a byte[], short[], or int[], with size a power of two, created by
   *       CompactHashing.createTable, whose values are either
   *       <ul>
   *         <li>UNSET, meaning "null pointer"
   *         <li>one plus an index into the entries and elements array

   */
  private static final int MAX_HASH_BUCKET_LENGTH = 9;

  // The way the `table`, `entries`, `keys`, and `values` arrays work together is as follows.
  //
  // The `table` array always has a size that is a power of 2. The hashcode of a key in the map
  // is masked in order to correspond to the current table size. For example, if the table size
  // is 128 then the mask is 127 == 0x7f, keeping the bottom 7 bits of the hash value.

    private @Nullable ValueEntry<K, V> lastEntry;

    ValueSet(@ParametricNullness K key, int expectedValues) {
      this.key = key;
      // Round expected values up to a power of 2 to get the table size.
      int tableSize = closedTableSize(expectedValues, VALUE_SET_LOAD_FACTOR);

      @SuppressWarnings({"rawtypes", "unchecked"})

    private @Nullable ValueEntry<K, V> lastEntry;

    ValueSet(@ParametricNullness K key, int expectedValues) {
      this.key = key;
      // Round expected values up to a power of 2 to get the table size.
      int tableSize = closedTableSize(expectedValues, VALUE_SET_LOAD_FACTOR);

      @SuppressWarnings({"rawtypes", "unchecked"})