.containsExactly(
            i1,
            i2,
            i3, // Integer subscribers are dispatched to first.
            s1,
            s2, // Though each integer subscriber dispatches to all string subscribers,
            s1,
            s2, // those string subscribers aren't actually dispatched to until all integer
            s1,
            s2 // subscribers have finished.
            )

    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() {

  }

  /**
   * 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}. */

    this.bus = bus;
    this.target = checkNotNull(target);
    this.method = method;
    method.setAccessible(true);

    this.executor = bus.executor();
  }

  /** Dispatches {@code event} to this subscriber using the proper executor. */
  final void dispatchEvent(Object event) {
    executor.execute(
        () -> {
          try {
            invokeSubscriberMethod(event);

// 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`.