}

  @Override
  public HashCode hashInt(int input) {
    return hashBytes(ByteBuffer.allocate(4).order(ByteOrder.LITTLE_ENDIAN).putInt(input).array());
  }

  @Override
  public HashCode hashLong(long input) {
    return hashBytes(ByteBuffer.allocate(8).order(ByteOrder.LITTLE_ENDIAN).putLong(input).array());
  }

  @Override
  public HashCode hashUnencodedChars(CharSequence input) {
    int len = input.length();

    void rejectsAnyNameReturnsFalse(String input) throws Exception {
        SmbFilenameFilter filter = (dir, name) -> false;

        boolean result = filter.accept(mockDir, input);

        assertFalse(result, "Filter should reject any provided name");
        verifyNoInteractions(mockDir);
    }

    /**
     * Edge: name-based filter behavior for diverse inputs.
     */
    @ParameterizedTest

  private static final class ByteArrayDataInputStream implements ByteArrayDataInput {
    final DataInput input;

    ByteArrayDataInputStream(ByteArrayInputStream byteArrayInputStream) {
      this.input = new DataInputStream(byteArrayInputStream);
    }

    @Override
    public void readFully(byte[] b) {
      try {
        input.readFully(b);
      } catch (IOException e) {
        throw new IllegalStateException(e);
      }

      Iterable<? extends T>... inputs) {
    for (Iterable<? extends T> input : inputs) {
      checkNotNull(input);
    }
    return new FluentIterable<T>() {
      @Override
      public Iterator<T> iterator() {
        return Iterators.concat(
            /* lazily generate the iterators on each input only as needed */

      Iterable<? extends T>... inputs) {
    for (Iterable<? extends T> input : inputs) {
      checkNotNull(input);
    }
    return new FluentIterable<T>() {
      @Override
      public Iterator<T> iterator() {
        return Iterators.concat(
            /* lazily generate the iterators on each input only as needed */

Let's say you have a Pydantic model with default values, like this one:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### Model for Input { #model-for-input }

If you use this model as an input like here:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

  }

  private static void testSortDescending(byte[] input, byte[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    SignedBytes.sortDescending(input);
    assertThat(input).isEqualTo(expectedOutput);
  }

  private static void testSortDescending(
      byte[] input, int fromIndex, int toIndex, byte[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);

  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};
    std::unique_ptr<TF_WhileParams> params(new TF_WhileParams(
        TF_NewWhile(func_graph_, &inputs[0], inputs.size(), s_)));

   *       predicate.apply(b))}.
   * </ul>
   *
   * @throws NullPointerException if {@code input} is null and this predicate does not accept null
   *     arguments
   */
  boolean apply(@ParametricNullness T input);

  /**
   * Indicates whether another object is equal to this predicate.
   *
   * <p><b>Warning: do not depend</b> on the behavior of this method.
   *

 * Executor)} on the input step.
 *
 * <h4>Catching</h4>
 *
 * To derive the next step from a failed input step, call {@link #catching(Class, ClosingFunction,
 * Executor)} or {@link #catchingAsync(Class, AsyncClosingFunction, Executor)} on the input step.
 *
 * <h4>Combining</h4>
 *
 * To derive a {@code ClosingFuture} from two or more input steps, pass the input steps to {@link