* to implement the related methods as well. Finally, two collection views are provided: {@link
 * #elementSet} contains the distinct elements of the multiset "with duplicates collapsed", and
 * {@link #entrySet} is similar but contains {@link Entry Multiset.Entry} instances, each providing
 * both a distinct element and the count of that element.
 *

   * collisions.
   *
   * @param keys arbitrary non-null keys
   * @return the stripes corresponding to the objects (one per each object, derived by delegating to
   *     {@link #get(Object)}; may contain duplicates), in an increasing index order.
   */
  public Iterable<L> bulkGet(Iterable<? extends Object> keys) {
    // Initially using the list to store the keys, then reusing it to store the respective L's

    }

    @Override
    public boolean contains(@Nullable Object obj) {
      return containsColumn(obj);
    }
  }

  /** Creates an iterator that returns each column value with duplicates omitted. */
  Iterator<C> createColumnKeyIterator() {
    return new ColumnKeyIterator();
  }

  private final class ColumnKeyIterator extends AbstractIterator<C> {

    assertIntact(q);
    q.remove(9);
    q.remove(11);
    q.remove(10);
    // Now we're in the critical state: [1, 15, 13, 8, 14]
    // Removing 8 while iterating caused duplicates in iteration result.
    List<Integer> result = Lists.newArrayListWithCapacity(initial.size());
    for (Iterator<Integer> iter = q.iterator(); iter.hasNext(); ) {
      Integer value = iter.next();
      result.add(value);

   * whose elements are the result of applying {@code elementFunction} to the inputs, with counts
   * equal to the result of applying {@code countFunction} to the inputs.
   *
   * <p>If the mapped elements contain duplicates (according to {@code comparator}), the first
   * occurrence in encounter order appears in the resulting multiset, with count equal to the sum of

    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.
    # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates
    default_cc_opt_flags = '-Wno-sign-compare'
  question = ('Please specify optimization flags to use during compilation when'
              ' bazel option "--config=opt" is specified [Default is %s]: '

			hi := lo
			if p.peek() == '-' {
				p.next()
				hi = p.registerNumber(p.next().String())
			}
			if hi < lo {
				lo, hi = hi, lo
			}
			// Check there are no duplicates in the register list.
			for i := 0; lo <= hi && i < maxReg; i++ {
				if bits&(1<<lo) != 0 {
					p.errorf("register R%d already in list", lo)
				}
				bits |= 1 << lo
				lo++
			}
		default:

Don't profile the marked function.  This flag is deprecated.
</li>
<li>
<code>DUPOK</code> = 2
<br>
It is legal to have multiple instances of this symbol in a single binary.
The linker will choose one of the duplicates to use.
</li>
<li>
<code>NOSPLIT</code> = 4
<br>
(For <code>TEXT</code> items.)
Don't insert the preamble to check if the stack must be split.

				break
			}
		}

		if requestedVersions > 0 && requestedVersions == nVersions {
			merged = append(merged, versions[0]...)
			break
		}
	}

	// Sanity check. Enable if duplicates show up.
	if false {
		found := make(map[[16]byte]struct{})
		for _, ver := range merged {
			if _, ok := found[ver.header.VersionID]; ok {
				panic("found dupe")
			}

		for _, user := range q.Users {
			lookupRes, actualGroups, _ := sys.LDAPConfig.GetValidatedDNWithGroups(user)
			if lookupRes != nil {
				groupSet := set.CreateStringSet(actualGroups...)

				// duplicates can be overwritten, fetched groups should be identical.
				cleanQ.Users[lookupRes.NormDN] = groupSet
			}
			// Search for non-normalized DN as well for backward compatibility.
			if _, ok := cleanQ.Users[user]; !ok {