3. Dieses `yield from` weist die Funktion an, über das Ding namens `file_like` zu iterieren. Und dann für jeden iterierten Teil, diesen Teil so zurückzugeben, als wenn er aus dieser Generatorfunktion (`iterfile`) stammen würde.

    Es handelt sich also hier um eine Generatorfunktion, die die „generierende“ Arbeit intern auf etwas anderes überträgt.

3. Essa declaração `yield from` informa a função para iterar sobre essa coisa nomeada de `file_like`. E então, para cada parte iterada, fornece essa parte como se viesse dessa função geradora (`iterfile`).

    Então, é uma função geradora que transfere o trabalho de "geração" para alguma outra coisa interna.

3. This `yield from` tells the function to iterate over that thing named `file_like`. And then, for each part iterated, yield that part as coming from this generator function (`iterfile`).

    So, it is a generator function that transfers the "generating" work to something else internally.

    if (IPV4_DELIMITER_MATCHER.countIn(ipString) + 1 != IPV4_PART_COUNT) {
      return null; // Wrong number of parts
    }

    byte[] bytes = new byte[IPV4_PART_COUNT];
    int start = 0;
    // Iterate through the parts of the ip string.
    // Invariant: start is always the beginning of an octet.
    for (int i = 0; i < IPV4_PART_COUNT; i++) {
      int end = ipString.indexOf(IPV4_DELIMITER, start);
      if (end == -1) {

     */
    private void removeIdleConnections() {
        long now = System.currentTimeMillis();
        List<SmbTransportImpl> idle = new ArrayList<>();

        // Iterate through connections without synchronization - ConcurrentLinkedQueue is thread-safe
        for (SmbTransportImpl transport : connections) {
            try {
                // Check if connection has been idle too long

*   Introduce ops for batching/unbatching tensors across Session::Run() calls.
*   Add tf.log_sigmoid(x) = tf.log(tf.sigmoid(x)) = -tf.nn.softplus(-x).
*   Changed hooks lists to immutable tuples, and now allow any iterable for the
    associated arguments.
*   Introduce TFDecorator.
*   Added an Mfcc op for speech feature generation.
*   Improved DirectSession::Run() overhead and error checking. Feeding a value

    if (IPV4_DELIMITER_MATCHER.countIn(ipString) + 1 != IPV4_PART_COUNT) {
      return null; // Wrong number of parts
    }

    byte[] bytes = new byte[IPV4_PART_COUNT];
    int start = 0;
    // Iterate through the parts of the ip string.
    // Invariant: start is always the beginning of an octet.
    for (int i = 0; i < IPV4_PART_COUNT; i++) {
      int end = ipString.indexOf(IPV4_DELIMITER, start);
      if (end == -1) {

        fireEvent(ResolutionListener.TEST_ARTIFACT, listeners, node);

        Object key = node.getKey();

        // TODO Does this check need to happen here? Had to add the same call
        // below when we iterate on child nodes -- will that suffice?
        if (managedVersions.containsKey(key)) {
            manageArtifact(node, managedVersions, listeners);
        }

            }
        }
        return documentItems;
    }

    /**
     * Performs a scroll search for processing large result sets efficiently.
     *
     * This method uses OpenSearch scroll API to iterate through large numbers of
     * documents without loading them all into memory at once.
     *
     * @param params The search request parameters
     * @param cursor Function to process each document in the result set

   * to do so leaks open files!
   */
  @Synchronized
  @Throws(IOException::class)
  fun snapshots(): MutableIterator<Snapshot> {
    initialize()
    return object : MutableIterator<Snapshot> {
      /** Iterate a copy of the entries to defend against concurrent modification errors. */
      private val delegate = ArrayList(lruEntries.values).iterator()