# opts in to modular op registration support by default.
build --define framework_shared_object=true
build --define tsl_protobuf_header_only=true

build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true

build --spawn_strategy=standalone
build -c opt

# Make Bazel print out all options from rc files.
build --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed

  DCHECK(tf_results->missing_unused_key_names_data.empty());

  size_t size = results.missing_unused_input_map_keys.size();
  tf_results->missing_unused_key_names.resize(size);
  tf_results->missing_unused_key_indexes.resize(size);

  for (int i = 0; i < size; ++i) {
    TensorId id = results.missing_unused_input_map_keys[i];
    tf_results->missing_unused_key_names_data.emplace_back(id.first);

      E element = (E) requireNonNull(elements[0]);
      return new SingletonImmutableSet<E>(element);
    } else if (chooseTableSize(uniques) < tableSize / 2) {
      // Resize the table when the array includes too many duplicates.
      return construct(uniques, elements);
    } else {
      @Nullable
      Object[] uniqueElements =

    *   Added gradient for `SparseToDense` op.
    *   Expose a flag that allows the number of threads to vary across Python
        benchmarks.
    *   `image.resize` in 2.0 now supports gradients for the new resize kernels.
    *   `image.resize` now considers proper pixel centers and has new kernels
        (incl. anti-aliasing).
    *   Renamed `tf.image` functions to remove duplicate "image" where it is
        redundant.

      reversedList = tmp;
    }
    return reversedList;
  }

  // TODO(user): move parts into a default method on ListenableFuture?
  @Override
  public String toString() {
    // TODO(cpovirk): Presize to something plausible?
    StringBuilder builder = new StringBuilder();
    if (getClass().getName().startsWith("com.google.common.util.concurrent.")) {
      builder.append(getClass().getSimpleName());
    } else {

		stream, err := sio.AES_256_GCM.Stream(key[:])
		if err != nil {
			bugLogIf(ctx, err)
			return
		}
		// Zero nonce, we only use each key once, and 32 bytes is plenty.
		nonce := make([]byte, stream.NonceSize())
		encw := stream.EncryptWriter(w, nonce, nil)
		defer encw.Close()

		// Initialize a zip writer which will provide a zipped content
		// of profiling data of all nodes
		inspectZipW = zip.NewWriter(encw)

- `PodSpec.Container.Resources` became mutable for CPU and memory resource types.
  - `PodSpec.Container.ResizePolicy` (new object) gives users control over how their containers are resized.
  - `PodStatus.Resize` status describes the state of a requested Pod resize.
  - `PodStatus.ResourcesAllocated` describes node resources allocated to Pod.
  - `PodStatus.Resources` describes node resources applied to running containers by CRI.

  // Fetch the shape and validate it is 2 by -1.
  num_dims = TF_GraphGetTensorNumDims(graph, feed_out_0, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(2, num_dims);

  // Resize the dimension vector appropriately.
  int64_t returned_dims[2];
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);