type: object
                    name:
                      description: Name of the subset.
                      type: string
                    trafficPolicy:
                      description: Traffic policies that apply to this subset.
                      properties:
                        connectionPool:
                          properties:

                      type: object
                    name:
                      description: Name of the subset.
                      type: string
                    trafficPolicy:
                      description: Traffic policies that apply to this subset.
                      properties:
                        connectionPool:
                          properties:

                      type: object
                    name:
                      description: Name of the subset.
                      type: string
                    trafficPolicy:
                      description: Traffic policies that apply to this subset.
                      properties:
                        connectionPool:
                          properties:

Note, most python users will want to use the Python `Tensor.__getitem__`
or `Variable.__getitem__` rather than this op directly.

The goal of this op is to produce a new tensor with a subset of
the elements from the `n` dimensional `input` tensor. The subset is chosen using
a sequence of `m` sparse range specifications encoded into the arguments
of this function. Note, in some cases

minReadySeconds) the old DaemonSet pod on that node is marked deleted. If the old pod becomes unavailable for any reason (Ready transitions to false, is evicted, or is drained) an updated pod is immediatedly created on that node without considering surge limits. Allowing surge implies the possibility that the resources consumed by the daemonset on any given node can double if the readiness check fails, and so resource intensive daemonsets should take into account that they may cause evictions during disruption."...

        `tf.keras.layers.EinsumDense`.
    *   Added `tf.keras.utils.audio_dataset_from_directory` utility to easily
        generate audio classification datasets from directories of `.wav` files.
    *   Added `subset="both"` support in
        `tf.keras.utils.image_dataset_from_directory`,`tf.keras.utils.text_dataset_from_directory`,
        and `audio_dataset_from_directory`, to be used with the

	errList := ValidateEndpoints(updatedEndpoint)
	errList = append(errList, ValidateEndpointsUpdate(updatedEndpoint, oldEndpoint)...)
	if len(errList) != 0 {
		t.Error("Endpoint should allow changing of Subset.Addresses.NodeName on update")
	}
}

func TestEndpointAddressNodeNameInvalidDNSSubdomain(t *testing.T) {
	// Check NodeName DNS validation
	endpoint := newNodeNameEndpoint("illegal*.nodename")