}

        return "Sent log notifications: " + events.size() + " events.";
    }

    /**
     * Formats a list of log notification events into a human-readable summary string.
     *
     * @param events the list of log notification events
     * @param maxDetailsLength the maximum length of the details string
     * @param maxDisplayEvents the maximum number of events to display

  }

  /**
   * Returns a supplier that always supplies {@code instance}.
   *
   * <p><b>Discouraged:</b> Prefer using {@code () -> instance}, but note that lambdas do not have
   * human-readable {@link #toString()} representations and are not serializable. If you need a
   * supplier that is serializable, use {@code (Supplier<T> & Serializable) () -> instance}.
   */

  }

  /**
   * Returns a supplier that always supplies {@code instance}.
   *
   * <p><b>Discouraged:</b> Prefer using {@code () -> instance}, but note that lambdas do not have
   * human-readable {@link #toString()} representations and are not serializable. If you need a
   * supplier that is serializable, use {@code (Supplier<T> & Serializable) () -> instance}.
   */

                        try {
                            while (!reader.ready()) {
                                ThreadUtil.sleep(1000L);
                            }
                            command = reader.readLine().trim();
                            if (logger.isDebugEnabled()) {
                                logger.debug("Process command: command={}", command);
                            }

    extends AbstractMap<K, V> implements ConcurrentMap<K, V>, Serializable {

  /*
   * The basic strategy is to subdivide the table among Segments, each of which itself is a
   * concurrently readable hash table. The map supports non-blocking reads and concurrent writes
   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The

    extends AbstractMap<K, V> implements ConcurrentMap<K, V>, Serializable {

  /*
   * The basic strategy is to subdivide the table among Segments, each of which itself is a
   * concurrently readable hash table. The map supports non-blocking reads and concurrent writes
   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The

final class LocalCache<K, V> extends AbstractMap<K, V> implements ConcurrentMap<K, V> {

  /*
   * The basic strategy is to subdivide the table among Segments, each of which itself is a
   * concurrently readable hash table. The map supports non-blocking reads and concurrent writes
   * across different segments.
   *
   * If a maximum size is specified, a best-effort bounding is performed per segment, using a

final class LocalCache<K, V> extends AbstractMap<K, V> implements ConcurrentMap<K, V> {

  /*
   * The basic strategy is to subdivide the table among Segments, each of which itself is a
   * concurrently readable hash table. The map supports non-blocking reads and concurrent writes
   * across different segments.
   *
   * If a maximum size is specified, a best-effort bounding is performed per segment, using a

        which could be challenging to read through, while not being actionable
        for end users. As of TF 2.7, TensorFlow filters internal frames in most
        errors that it raises, to keep stack traces short, readable, and focused
        on what's actionable for end users (their own code).

    This behavior can be disabled by calling
    `tf.debugging.disable_traceback_filtering()`, and can be re-enabled via