@NullUnmarked
public class DoubleMathBenchmark {
  private static final double[] positiveDoubles = new double[ARRAY_SIZE];
  private static final int[] factorials = new int[ARRAY_SIZE];
  private static final double[] doubles = new double[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positiveDoubles[i] = randomPositiveDouble();
      doubles[i] = randomDouble(Long.SIZE);

@NullUnmarked
public class DoubleMathBenchmark {
  private static final double[] positiveDoubles = new double[ARRAY_SIZE];
  private static final int[] factorials = new int[ARRAY_SIZE];
  private static final double[] doubles = new double[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positiveDoubles[i] = randomPositiveDouble();
      doubles[i] = randomDouble(Long.SIZE);

import jsinterop.annotations.JsPackage;

/** Web specializations for {@link Doubles} methods. */
public abstract class DoublesMethodsForWeb {

  @JsMethod(name = "Math.min", namespace = JsPackage.GLOBAL)
  public static native double min(double... array);

  @JsMethod(name = "Math.max", namespace = JsPackage.GLOBAL)
  public static native double max(double... array);

 * the License.
 */

package com.google.common.primitives;

import com.google.common.annotations.GwtCompatible;

/**
 * Holder for web specializations of methods of {@code Doubles}. Intended to be empty for regular
 * version.
 */
@GwtCompatible

    @Override
    protected List<Double> create(Double[] elements) {
      return asList(elements);
    }
  }

  public static final class DoublesAsListHeadSubListGenerator extends TestDoubleListGenerator {
    @Override
    protected List<Double> create(Double[] elements) {
      Double[] suffix = {Double.MIN_VALUE, Double.MAX_VALUE};
      Double[] all = concat(elements, suffix);

TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx,
                                         const tensorflow::tstring& value);

// Return a tensor handle containing a 2x2 matrix of doubles
TFE_TensorHandle* DoubleTestMatrixTensorHandle(TFE_Context* ctx);

// Return a tensor handle containing a 2x2 matrix of floats
TFE_TensorHandle* TestMatrixTensorHandle(TFE_Context* ctx);

 *
 * <ul>
 *   <li>{@link Booleans}
 *   <li>{@link Bytes}
 *       <ul>
 *         <li>{@link SignedBytes}
 *         <li>{@link UnsignedBytes}
 *       </ul>
 *   <li>{@link Chars}
 *   <li>{@link Doubles}
 *   <li>{@link Floats}
 *   <li>{@link Ints}
 *       <ul>
 *         <li>{@link UnsignedInts}
 *       </ul>
 *   <li>{@link Longs}
 *       <ul>
 *         <li>{@link UnsignedLongs}
 *       </ul>

import static com.google.common.base.Preconditions.checkArgument;
import static java.lang.Double.MAX_EXPONENT;
import static java.lang.Double.MIN_EXPONENT;
import static java.lang.Double.POSITIVE_INFINITY;
import static java.lang.Double.doubleToRawLongBits;
import static java.lang.Double.isNaN;
import static java.lang.Double.longBitsToDouble;
import static java.lang.Math.getExponent;
import static java.lang.Math.max;

 *       create a {@link SettableFuture} instead. (If your needs are more complex, you may prefer
 *       {@link AbstractFuture}.)
 * </ul>
 *
 * <p><b>Test doubles</b>: If you need a {@code ListenableFuture} for your test, try a {@link
 * SettableFuture} or one of the methods in the {@link Futures#immediateFuture Futures.immediate*}

 *       create a {@link SettableFuture} instead. (If your needs are more complex, you may prefer
 *       {@link AbstractFuture}.)
 * </ul>
 *
 * <p><b>Test doubles</b>: If you need a {@code ListenableFuture} for your test, try a {@link
 * SettableFuture} or one of the methods in the {@link Futures#immediateFuture Futures.immediate*}