* Tests the {@link Map} implementations of {@link java.util}, suppressing tests that trip known
 * bugs in OpenJDK 6 or higher.
 *
 * @author Kevin Bourrillion
 */
// TODO(cpovirk): consider renaming this class in light of our now running it under newer JDKs.
public class OpenJdk6MapTests extends TestsForMapsInJavaUtil {
  public static Test suite() {
    return new OpenJdk6MapTests().allTests();
  }

  @Override

   * </ul>
   *
   * <p>This assumes that any non-null objects passed to this function conform to the {@code
   * equals()} contract.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated; use {@link
   * java.util.Objects#equals} instead.
   */
  public static boolean equal(@CheckForNull Object a, @CheckForNull Object b) {

[IP] now implements the [encoding.TextAppender] interface....

Templates now support range-over-func and range-over-int....

libcudnn9-dev-cuda-12=9.1.1.17-1
libcudnn9-cuda-12=9.1.1.17-1

# This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image.
# For now it ensures that we install at least version 12.3.107 of PTXAS,
# since 12.3.103 has a bug.

		t.Errorf("Expected to get back a nil Author but got: %v", hnPost.Author)
	}

	now := time.Now().Round(time.Second)
	NewPost := HNPost{
		BasePost: &BasePost{Title: "embedded_pointer_type2"},
		Author: &Author{
			Name:        "test",
			Content:     Content{"test"},
			ContentPtr:  nil,
			Birthday:    now,
			BirthdayPtr: nil,
		},
	}
	DB.Create(&NewPost)

	hnPost = HNPost{}

The value returned by [sha1.New] now also implements the [encoding.BinaryAppender] interface....

[Regexp] now implements the [encoding.TextAppender] interface....

The values returned by [New] and [NewIEEE] now also implement the [encoding.BinaryAppender] interface....

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML