import com.google.common.annotations.GwtCompatible;
import java.lang.annotation.Retention;
import java.lang.annotation.Target;

/**
 * Annotates a "top-level" type-variable usage that takes its nullness from the type argument
 * supplied by the user of the class. For example, {@code Multiset.Entry.getElement()} returns
 * {@code @ParametricNullness E}, which means:
 *
 * <ul>

    }
    requests.addAndGet(reps);
    return dummy;
  }

  private int nextRandomKey() {
    int a = random.nextInt(max);

    /*
     * For example, if concentration=2.0, the following takes the square root of
     * the uniformly-distributed random integer, then truncates any fractional
     * part, so higher integers would appear (in this case linearly) more often
     * than lower ones.
     */

import com.google.common.annotations.GwtCompatible;
import java.lang.annotation.Retention;
import java.lang.annotation.Target;

/**
 * Annotates a "top-level" type-variable usage that takes its nullness from the type argument
 * supplied by the user of the class. For example, {@code Multiset.Entry.getElement()} returns
 * {@code @ParametricNullness E}, which means:
 *
 * <ul>

import com.google.common.annotations.GwtCompatible;
import java.lang.annotation.Retention;
import java.lang.annotation.Target;

/**
 * Annotates a "top-level" type-variable usage that takes its nullness from the type argument
 * supplied by the user of the class. For example, {@code Multiset.Entry.getElement()} returns
 * {@code @ParametricNullness E}, which means:
 *
 * <ul>

import com.google.common.annotations.GwtCompatible;
import java.lang.annotation.Retention;
import java.lang.annotation.Target;

/**
 * Annotates a "top-level" type-variable usage that takes its nullness from the type argument
 * supplied by the user of the class. For example, {@code Multiset.Entry.getElement()} returns
 * {@code @ParametricNullness E}, which means:
 *
 * <ul>

//       .Attr("N: int >= 2")
//       .Attr("T: type");
// that defines two inputs, "concat_dim" and "values" (in that order).
// You must use TF_AddInput() for the first input (since it takes a
// single tensor), and TF_AddInputList() for the second input (since
// it takes a list, even if you were to pass a list with a single
// tensor), as in:
//   TF_OperationDescription* desc = TF_NewOperation(graph, "Concat", "c");

import java.util.concurrent.CancellationException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeoutException;
import org.jspecify.annotations.NullUnmarked;

/** A benchmark that times how long it takes to add a given number of */
@VmOptions({"-Xms8g", "-Xmx8g"})
@NullUnmarked
public class SingleThreadAbstractFutureBenchmark {
  @Param Impl impl;

  private final Exception exception = new Exception();

  }

  companion object {
    /**
     * The timeout to use while discarding a stream of input data. Since this is used for connection
     * reuse, this timeout should be significantly less than the time it takes to establish a new
     * connection.
     */
    const val DISCARD_STREAM_TIMEOUT_MILLIS = 100
  }

import com.google.common.annotations.GwtCompatible;
import java.lang.annotation.Retention;
import java.lang.annotation.Target;

/**
 * Annotates a "top-level" type-variable usage that takes its nullness from the type argument
 * supplied by the user of the class. For example, {@code Multiset.Entry.getElement()} returns
 * {@code @ParametricNullness E}, which means:
 *
 * <ul>

    }
    requests.addAndGet(reps);
    return dummy;
  }

  private int nextRandomKey() {
    int a = random.nextInt(max);

    /*
     * For example, if concentration=2.0, the following takes the square root of
     * the uniformly-distributed random integer, then truncates any fractional
     * part, so higher integers would appear (in this case linearly) more often
     * than lower ones.
     */