*
 * @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();

        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

  @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);
  }

 */
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() {

  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",

            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:

                    <mxGeometry relative="1" as="geometry">
                        <Array as="points">
                            <mxPoint x="800" y="521"/>
                            <mxPoint x="800" y="560"/>
                        </Array>
                        <mxPoint x="803" y="521" as="sourcePoint"/>
                    </mxGeometry>
                </mxCell>

    if (toLessThanMid == midLessThanFrom) {
      // Either array[to] < array[mid] < array[from] or array[from] <= array[mid] <= array[to].
      swap(array, mid, from);
    } else if (toLessThanMid != toLessThanFrom) {
      // Either array[from] <= array[to] < array[mid] or array[mid] <= array[to] < array[from].
      swap(array, from, to);
    }