import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.util.Arrays;
import java.util.Comparator;
import java.util.Random;

/**
 * A benchmark to determine the overhead of sorting with {@link Ordering#from(Comparator)}, or with
 * {@link Ordering#natural()}, as opposed to using the inlined {@link Arrays#sort(Object[])}
 * implementation, which uses {@link Comparable#compareTo} directly.
 *

    private final List<EventSpy> eventSpies;

    @Inject
    public EventSpyDispatcher(List<EventSpy> eventSpies) {
        // make copy to get rid of needless overhead for dynamic lookups
        this.eventSpies = new ArrayList<>(eventSpies);
    }

    public ExecutionListener chainListener(ExecutionListener listener) {
        if (eventSpies.isEmpty()) {
            return listener;

  }

  /**
   * Returns the current elapsed time shown on this stopwatch, expressed in the desired time unit,
   * with any fraction rounded down.
   *
   * <p><b>Note:</b> the overhead of measurement can be more than a microsecond, so it is generally
   * not useful to specify {@link TimeUnit#NANOSECONDS} precision here.
   *

 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code long[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

    test to timeout but it could be useful when you need to execute a single
    test or more in general your filtered/selected tests have a very low
    execution time and the sharding
    [could create an overhead on the test execution](https://github.com/bazelbuild/bazel/issues/2113#issuecomment-264054799).

2.  Using [Docker](https://www.docker.com) and TensorFlow's CI scripts.

    ```bash

 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code double[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

            [eager context](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/eager/context.py).
        *   Eager performance should be similar with this feature enabled.
            *   A roughly 5us per-op overhead may be observed when running many
                small functions.
            *   Note a
                [known issue](https://github.com/tensorflow/tensorflow/issues/55414)
                with GPU performance.

setting](/pkg/crypto/tls/#ConnectionState.ExportKeyingMaterial).

Go 1.22 changed how the runtime interacts with transparent huge pages on Linux.
In particular, a common default Linux kernel configuration can result in
significant memory overheads, and Go 1.22 no longer works around this default.
To work around this issue without adjusting kernel settings, transparent huge
pages can be disabled for Go memory with the