array[i] = counter.getAndIncrement();
        }
        builder.addAll(ImmutableDoubleArray.copyOf(array));
      }
    },
    ADD_LARGER_ARRAY {
      @Override
      void doIt(ImmutableDoubleArray.Builder builder, AtomicInteger counter) {
        double[] array = new double[RANDOM.nextInt(200) + 200];
        for (int i = 0; i < array.length; i++) {
          array[i] = counter.getAndIncrement();

 *
 * @author Louis Wasserman
 */
public class IntMathRoundingBenchmark {
  private static final int[] positive = new int[ARRAY_SIZE];
  private static final int[] nonzero = new int[ARRAY_SIZE];
  private static final int[] ints = new int[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positive[i] = randomPositiveBigInteger(Integer.SIZE - 2).intValue();

  RoundingMode mode;

  private static final long[] positive = new long[ARRAY_SIZE];
  private static final long[] nonzero = new long[ARRAY_SIZE];
  private static final long[] longs = new long[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positive[i] = randomPositiveBigInteger(Long.SIZE - 2).longValue();

  @CollectionSize.Require(absent = {ZERO, ONE})
  public void testCreateWithDuplicates_nullDuplicatesNotRejected() {
    E[] array = createArrayWithNullElement();
    array[0] = null;
    collection = getSubjectGenerator().create(array);

    List<E> expectedWithDuplicateRemoved = Arrays.asList(array).subList(1, getNumElements());
    expectContents(expectedWithDuplicateRemoved);
  }

        builder.add(counter.getAndIncrement());
      }
    },
    ADD_ARRAY {
      @Override
      void doIt(ImmutableLongArray.Builder builder, AtomicLong counter) {
        long[] array = new long[RANDOM.nextInt(10)];
        for (int i = 0; i < array.length; i++) {
          array[i] = counter.getAndIncrement();
        }
        builder.addAll(array);
      }
    },
    ADD_COLLECTION {
      @Override

 */
public class IntMathBenchmark {
  private static int[] exponent = new int[ARRAY_SIZE];
  private static int[] factorial = new int[ARRAY_SIZE];
  private static int[] binomial = new int[ARRAY_SIZE];
  private static final int[] positive = new int[ARRAY_SIZE];
  private static final int[] nonnegative = new int[ARRAY_SIZE];
  private static final int[] ints = new int[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {

            return source;
        }
        final char[] array = source.toCharArray();
        for (int i = 0; i < array.length; ++i) {
            switch (array[i]) {
            case WAVE_DASH:
                array[i] = FULLWIDTH_TILDE;
                break;
            case DOUBLE_VERTICAL_LINE:
                array[i] = PARALLEL_TO;
                break;
            case MINUS_SIGN:

  public void testRetainAll_duplicatesKept() {
    E[] array = createSamplesArray();
    array[1] = e0();
    collection = getSubjectGenerator().create(array);
    assertFalse(
        "containsDuplicates.retainAll(superset) should return false",
        collection.retainAll(MinimalCollection.of(createSamplesArray())));
    expectContents(array);
  }

  @CollectionFeature.Require(SUPPORTS_REMOVE)

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

cc_library(
    name = "array_ops",
    srcs = [
        "array_ops.cc",
    ],
    hdrs = [
        "array_ops.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",

/**
 * Simple helper class to build a "sparse" array of objects based on the indexes that were added to
 * it. The array will be from 0 to the maximum index given. All non-set indexes will contain null
 * (so it's not really a sparse array, just a pseudo sparse array). The builder can also return a
 * CharEscaper based on the generated array.
 *
 * @author Sven Mawson
 * @since 15.0
 */
@GwtCompatible