* Pod spec is mutable when the pod is uninitialized. The API server requires the pod spec to be valid even if it's uninitialized. Updating the status field of uninitialized pods is invalid.([#51733](https://github.com/kubernetes/kubernetes/pull/51733))

// Creates a TF_WhileParams for creating a while loop in `g`. `inputs` are
// outputs that already exist in `g` used as initial values for the loop
// variables.
//
// The returned TF_WhileParams will have all fields initialized except
// `cond_output`, `body_outputs`, and `name`. The `body_outputs` buffer will be
// allocated to size `ninputs`. The caller should build `cond_graph` and

	_, err = obj.NewMultipartUpload(context.Background(), bucket, object, opts)
	if err == nil {
		t.Fatalf("%s: Expected to fail since the NewMultipartUpload is initialized on a non-existent bucket.", instanceType)
	}
	if errMsg != err.Error() {
		t.Errorf("%s, Expected to fail with Error \"%s\", but instead found \"%s\".", instanceType, errMsg, err.Error())
	}

		return ObjectInfo{}, toObjectErr(errInvalidArgument)
	}

	// Initialize parts metadata
	partsMetadata := make([]FileInfo, len(storageDisks))

	fi := newFileInfo(pathJoin(minioMetaBucket, key), dataDrives, parityDrives)
	fi.DataDir = mustGetUUID()

	// Initialize erasure metadata.
	for index := range partsMetadata {
		partsMetadata[index] = fi
	}

  // More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  // +optional
  optional Probe readinessProbe = 11;

  // StartupProbe indicates that the Pod has successfully initialized.
  // If specified, no other probes are executed until this completes successfully.
  // If this probe fails, the Pod will be restarted, just as if the livenessProbe failed.

    * Any code that inspects this annotation should be changed to use the new key.
      State of Initialization will continue to be reported in both pods.alpha.kubernetes.io/initialized
      and in `podStatus.conditions.{status: "True", type: Initialized}`

	for i, n := range names {
		fmt.Fprintf(&b, "__typeof__(%s) *__cgo__%d;\n", n.C, i)
		if n.Kind == "iconst" {
			fmt.Fprintf(&b, "enum { __cgo_enum__%d = %s };\n", i, n.C)
		}
	}

	// We create a data block initialized with the values,
	// so we can read them out of the object file.
	fmt.Fprintf(&b, "long long __cgodebug_ints[] = {\n")
	for _, n := range names {
		if n.Kind == "iconst" {
			fmt.Fprintf(&b, "\t%s,\n", n.C)

*   RNG behavior change for `tf.keras.initializers`. Keras initializers will now
    use stateless random ops to generate random numbers.
    *   Both seeded and unseeded initializers will always generate the same
        values every time they are called (for a given variable shape). For
        unseeded initializers (`seed=None`), a random seed will be created and
        assigned at initializer creation (different initializer instances get

        protected Class<T> cls;

        protected Consumer<T> initializer;

        protected StandardCrawlerContainer container;

        private T instance;

        protected ComponentDef(final Class<T> cls, final Consumer<T> initializer, final StandardCrawlerContainer container) {
            this.cls = cls;
            this.initializer = initializer;
            this.container = container;
        }

  virtual absl::Status SetOrUpdateServerDef(
      const ServerDef& server_def, bool reset_context, int keep_alive_secs,
      int64_t init_timeout_in_ms, int retries,
      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created
  // for remote workers. Currently this only works for resetting context.
  // TODO(b/289445025): Consider removing this when we find a proper fix.