- Support [service.beta.kubernetes.io/azure-pip-ip-tags] annotations to allow customers to specify ip-tags to influence public-ip creation in Azure [Tag1=Value1, Tag2=Value2, etc.] ([#94114](https://github.com/kubernetes/kubernetes/pull/94114), [@MarcPow](https://github.com/MarcPow)) [SIG Cloud Provider]

```
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- Provide links to your updated versions of the above two colab notebooks.

 Plugins should avoid these classes and be updated to use only Maven3 dependencies (and require Maven3): see
 {{{https://cwiki.apache.org/confluence/display/MAVEN/Plugin+migration+to+Maven3+dependencies} Plugin migration to Maven3 dependencies}}

// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.

   * use the {@code ArrayList} {@linkplain ArrayList#ArrayList() constructor} directly, taking
   * advantage of <a
   * href="https://docs.oracle.com/javase/tutorial/java/generics/genTypeInference.html#type-inference-instantiation">"diamond"
   * syntax</a>.
   */
  @SuppressWarnings("NonApiType") // acts as a direct substitute for a constructor call
  public static <E extends @Nullable Object> ArrayList<E> newArrayList() {

inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)
are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack

“parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training and inference on deep neural networks. Several Google services use TensorFlow in production, we have released it as an open-source project, and it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and...

struct TF_Library {
  void* lib_handle;
  TF_Buffer op_list;
};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

[dev-ml-list]: https://maven.apache.org/mailing-lists.html
[code-style]: https://maven.apache.org/developers/conventions/code.html
[cla]: https://www.apache.org/licenses/#clas
[maven-wiki]: https://cwiki.apache.org/confluence/display/MAVEN/Index

  @Override
  public int hashCode() {
    return Sets.hashCodeImpl(this);
  }

  // This declaration is needed to make Set.iterator() and
  // ImmutableCollection.iterator() appear consistent to javac's type inference.
  @Override
  public abstract UnmodifiableIterator<E> iterator();

  abstract static class CachingAsList<E> extends ImmutableSet<E> {
    @LazyInit private transient ImmutableList<E> asList;

    @Override