+ " even if some elements are null.",
        getSet().equals(MinimalSet.from(elements)));
  }

  @CollectionSize.Require(absent = CollectionSize.ZERO)
  public void testEquals_otherContainsNull() {
    Collection<E> elements = getSampleElements(getNumElements() - 1);
    elements.add(null);
    Set<E> other = MinimalSet.from(elements);

    assertFalse(

            + " even if some elements are null.",
        getSet().equals(MinimalSet.from(elements)));
  }

  @CollectionSize.Require(absent = CollectionSize.ZERO)
  public void testEquals_otherContainsNull() {
    Collection<E> elements = getSampleElements(getNumElements() - 1);
    elements.add(null);
    Set<E> other = MinimalSet.from(elements);

    assertFalse(

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

     */
    task.addListener(() -> scheduled.cancel(false), directExecutor());
    return task;
  }

  /**
   * Returns a {@code Future} whose result is taken from the given primary {@code input} or, if the
   * primary input fails with the given {@code exceptionType}, from the result provided by the
   * {@code fallback}. {@link Function#apply} is not invoked until the primary input has failed, so

    private static final String X_ROBOTS_TAG = "X-Robots-Tag";

    /** XPath expression for extracting thumbnail content from meta tags */
    private static final String META_NAME_THUMBNAIL_CONTENT = "//META[@name=\"thumbnail\" or @name=\"THUMBNAIL\"]/@content";

    /** XPath expression for extracting Open Graph image content from meta tags */
    private static final String META_PROPERTY_OGIMAGE_CONTENT = "//META[@property=\"og:image\"]/@content";

		{Name: "subquery_raw_4", Age: 40},
	}
	DB.Create(&users)

	var count int64
	err := DB.Raw("select count(*) from (?) tmp where 1 = ? AND name IN (?)", DB.Raw("select name from users where age >= ? and name in (?)", 10, []string{"subquery_raw_1", "subquery_raw_2", "subquery_raw_3"}), 1, DB.Raw("select name from users where age >= ? and name in (?)", 20, []string{"subquery_raw_1", "subquery_raw_2", "subquery_raw_3"})).Scan(&count).Error

  }

  ImmutableSortedMultiset<E> getSubMultiset(int from, int to) {
    checkPositionIndexes(from, to, length);
    if (from == to) {
      return emptyMultiset(comparator());
    } else if (from == 0 && to == length) {
      return this;
    } else {
      RegularImmutableSortedSet<E> subElementSet = elementSet.getSubSet(from, to);
      return new RegularImmutableSortedMultiset<>(

     * @return a stream of substrings resulting from splitting the input string, or an empty stream if the input is {@code null}
     */
    public static StreamOf<String> split(final String value, final String regex) {
        return stream(value == null ? null : value.split(regex));
    }

    /**
     * Creates a stream of map entries from the given map.
     *
     * @param <K> the type of keys in the map

## Description from docstring { #description-from-docstring }

As descriptions tend to be long and cover multiple lines, you can declare the *path operation* description in the function <abbr title="a multi-line string as the first expression inside a function (not assigned to any variable) used for documentation">docstring</abbr> and **FastAPI** will read it from there.

     * @param fields the fields to extract from the query log
     * @param tagFieldNames the names of the fields to use as tags
     * @param roleFieldName the name of the field to use for roles
     * @param readingConverter the converter to use for reading values
     * @param normalizer the normalizer to use for normalizing values
     * @return a list of suggest items parsed from the query log
     */