* returning more-or-less the same answers.
 */
@NullUnmarked
@GwtIncompatible
@J2ktIncompatible
public class QuantilesAlgorithmTest extends TestCase {

  private static final Random rng = new Random(82674067L);
  private static final int DATASET_SIZE = 1000;
  private static final double ALLOWED_ERROR = 1.0e-10;
  private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;

 * returning more-or-less the same answers.
 */
@NullUnmarked
@GwtIncompatible
@J2ktIncompatible
public class QuantilesAlgorithmTest extends TestCase {

  private static final Random rng = new Random(82674067L);
  private static final int DATASET_SIZE = 1000;
  private static final double ALLOWED_ERROR = 1.0e-10;
  private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;

  }

  @SuppressWarnings("deprecation")
  public void testEncodedStringInputs() {
    Random rng = new Random(0);
    for (int z = 0; z < 100; z++) {
      int[] codePoints = new int[rng.nextInt(8)];
      for (int i = 0; i < codePoints.length; i++) {
        do {
          codePoints[i] = rng.nextInt(0x800);
        } while (!Character.isValidCodePoint(codePoints[i])

  }

  @SuppressWarnings("deprecation")
  public void testEncodedStringInputs() {
    Random rng = new Random(0);
    for (int z = 0; z < 100; z++) {
      int[] codePoints = new int[rng.nextInt(8)];
      for (int i = 0; i < codePoints.length; i++) {
        do {
          codePoints[i] = rng.nextInt(0x800);
        } while (!Character.isValidCodePoint(codePoints[i])

        passing a `dtype` argument to the layer.
    *   `tf.random.Generator` for keras initializers and all RNG code.
    *   Added 3 new APIs for enable/disable/check the usage of
        `tf.random.Generator` in keras backend, which will be the new backend
        for all the RNG in Keras. We plan to switch on the new code path by
        default in tf 2.8, and the behavior change will likely to cause some