* the iterator's own {@code add}, {@code set} or {@code remove} operations) the results of the
   * iteration are undefined.
   *
   * <p>The returned list is not serializable and does not have random access.
   */
  @Override
  public List<V> get(@ParametricNullness K key) {
    return new AbstractSequentialList<V>() {
      @Override
      public int size() {

* Fix the bug that query Kubelet's stats summary with CRI stats enabled results in error. ([#53107](https://github.com/kubernetes/kubernetes/pull/53107), [@Random-Liu](https://github.com/Random-Liu))

                <version>1.0.0</version>
            </project>
            """;

        Document doc = Document.of(pomXml);
        Element root = doc.root();

        // Insert elements in random order - they should be positioned correctly
        DomUtils.insertContentElement(root, "licenses", "");
        DomUtils.insertContentElement(root, "name", "Test Project");
        DomUtils.insertNewElement("dependencies", root);

            final byte[] addr = localInetAddress.getAddress();
            localHostname =
                    "JCIFS" + (addr[2] & 0xFF) + "_" + (addr[3] & 0xFF) + "_" + Hexdump.toHexString((int) (Math.random() * 0xFF), 2);
        }

        /*
         * Create an NbtAddress for the local interface with
         * the name deduced above possibly with scope applied and
         * cache it forever.
         */

	partsMetadata[0] = partsMetadataBackup // Revert before going to the next test

	// Test 3: Not synchronized DataDir
	erasureDisks = s.getDisks()
	partsMetadataBackup = partsMetadata[1]
	partsMetadata[1].DataDir = "foo-random"

	errs = make([]error, len(erasureDisks))
	_, _ = checkObjectWithAllParts(ctx, erasureDisks, partsMetadata,
		errs, fi, false, bucket, object, madmin.HealDeepScan)

	for diskIndex, disk := range erasureDisks {

* Fix TerminationMessagePath ([#23658](https://github.com/kubernetes/kubernetes/pull/23658), [@Random-Liu](https://github.com/Random-Liu))
* Fix gce.getDiskByNameUnknownZone logic. ([#24452](https://github.com/kubernetes/kubernetes/pull/24452), [@a-robinson](https://github.com/a-robinson))

  TF_Tensor* tensor_shape = Int32Tensor({37, 1});
  TF_Operation* shape = Const(tensor_shape, func_graph.get(), s.get(), "shape");
  TF_Operation* random =
      RandomUniform(shape, TF_FLOAT, func_graph.get(), s.get());

  TF_Output outputs[] = {{random, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name,
                             /*append_hash_to_fn_name=*/false, -1,

   * Returns a general-purpose, <b>temporary-use</b>, non-cryptographic hash function. The algorithm
   * the returned function implements is unspecified and subject to change without notice.
   *
   * <p><b>Warning:</b> a new random seed for these functions is chosen each time the {@code
   * Hashing} class is loaded. <b>Do not use this method</b> if hash codes may escape the current

Wenn das Programm nun Dinge in den Arbeitsspeicher lädt, zum Beispiel ein Modell für maschinelles Lernen in einer Variablen oder den Inhalt einer großen Datei in einer Variablen, verbraucht das alles **einen Teil des Arbeitsspeichers (RAM – Random Access Memory)** des Servers.

}

type repeatedByte struct {
	off int64
	b   byte
	n   int64
}

// rleBuffer is a run-length-encoded byte buffer.
// It's an io.Writer (like a bytes.Buffer) and also an io.ReaderAt,
// allowing random-access reads.
type rleBuffer struct {
	buf []repeatedByte
}

func (r *rleBuffer) Size() int64 {
	if len(r.buf) == 0 {
		return 0
	}
	last := &r.buf[len(r.buf)-1]
	return last.off + last.n
}