dirMatches := best.isDir() == other.isDir()
				suffixMatches := strings.HasSuffix(best.name, slashSeparator) == strings.HasSuffix(other.name, slashSeparator)

				// Simple case. Both are same type with same suffix.
				if dirMatches && suffixMatches {
					toMerge = append(toMerge, otherIdx)
					continue
				}

				if !dirMatches {

  }

  /**
   * Returns a dispatcher that dispatches events to subscribers immediately as they're posted
   * without using an intermediate queue to change the dispatch order. This is effectively a
   * depth-first dispatch order, vs. breadth-first when using a queue.
   */
  static Dispatcher immediate() {
    return ImmediateDispatcher.INSTANCE;
  }

  /** Dispatches the given {@code event} to the given {@code subscribers}. */

    checkNotNull(label, "label");
    synchronized (listeners) {
      for (PerListenerQueue<L> queue : listeners) {
        queue.add(event, label);
      }
    }
  }

  /**
   * Dispatches all events enqueued prior to this call, serially and in order, for every listener.
   *
   * <p>Note: this method is idempotent and safe to call from any thread
   */
  public void dispatch() {

import org.apache.maven.eventspy.EventSpy;
import org.apache.maven.execution.ExecutionListener;
import org.eclipse.aether.RepositoryListener;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * Dispatches callbacks to all registered EventSpies.
 * @since 3.0.2
 */
@Named
@Singleton
public class EventSpyDispatcher {
    private final Logger logger = LoggerFactory.getLogger(getClass());

// ReadWriter stores pointers to a [Reader] and a [Writer].
// It implements [io.ReadWriter].
type ReadWriter struct {
	*Reader
	*Writer
}

// NewReadWriter allocates a new [ReadWriter] that dispatches to r and w.
func NewReadWriter(r *Reader, w *Writer) *ReadWriter {
	return &ReadWriter{r, w}

    *   Removing of dtype in the constructor of initializers and partition_info
        in call.
    *   Add `tf.math.nextafter` op.
    *   Turn on MKL-DNN contraction kernels by default. MKL-DNN dynamically
        dispatches the best kernel implementation based on CPU vector
        architecture. To disable them, build with
        `--define=tensorflow_mkldnn_contraction_kernel=0`.