* <origin><![CDATA[
     * <distributionManagement>
     * <repository>
     * <id>some-repo</id>
     * <url>scp://host/path</url>
     * </repository>
     * <snapshotRepository>
     * <id>some-snap-repo</id>
     * <url>scp://host/snapshot-path</url>
     * </snapshotRepository>
     * </distributionManagement>
     * ]]></origin>
     * <usage><![CDATA[

    int i = 0;
    for (Object element : elements) {
      array[i++] = element;
    }
    return array;
  }

  /** Swaps {@code array[i]} with {@code array[j]}. */
  static void swap(Object[] array, int i, int j) {
    Object temp = array[i];
    array[i] = array[j];
    array[j] = temp;
  }

  @CanIgnoreReturnValue

    int i = 0;
    for (Object element : elements) {
      array[i++] = element;
    }
    return array;
  }

  /** Swaps {@code array[i]} with {@code array[j]}. */
  static void swap(Object[] array, int i, int j) {
    Object temp = array[i];
    array[i] = array[j];
    array[j] = temp;
  }

  @CanIgnoreReturnValue

    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about
    // twice as many reads and writes. But benchmarking shows that they usually perform better than

and
[issues tagged with `2.0`](https://github.com/tensorflow/tensorflow/issues?q=is%3Aopen+is%3Aissue+label%3A2.0)
on GitHub for insight into recent issues and development progress.

If you experience any snags when using TF 2.0, please let us know at the
[TF 2.0 Testing User Group](https://groups.google.com/a/tensorflow.org/forum/?utm_medium=email&utm_source=footer#!forum/testing).