return common.OpenAPIDefinition{
		Schema: spec.Schema{
			SchemaProps: spec.SchemaProps{
				Description: "Endpoint represents a single logical \"backend\" implementing a service.",
				Type:        []string{"object"},
				Properties: map[string]spec.Schema{
					"addresses": {
						VendorExtensible: spec.VendorExtensible{

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}

def TF_AllOp : TF_Op<"All", [Pure]> {
  let summary = [{
Computes the "logical and" of elements across dimensions of a tensor.
  }];

  let description = [{
Reduces `input` along the dimensions given in `axis`. Unless
`keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in

- Fixed issue on Windows when calculating cpu limits on nodes with more than 64 logical processors ([#114231](https://github.com/kubernetes/kubernetes/pull/114231), [@mweibel](https://github.com/mweibel))

          "type": "string"
        }
      },
      "type": "object"
    },
    "io.k8s.api.discovery.v1.Endpoint": {
      "description": "Endpoint represents a single logical \"backend\" implementing a service.",
      "properties": {
        "addresses": {

            is not there, it means they are off.

## Bug Fixes and Other Changes

*   New argument `experimental_device_ordinal` in `LogicalDeviceConfiguration`
    to control the order of logical devices (GPU only).

*   `tf.keras`:

    *   Changed the TensorBoard tag names produced by the
        `tf.keras.callbacks.TensorBoard` callback, so that summaries logged