}},
			},
		},
		"empty subsets": {
			endpoints: core.Endpoints{
				ObjectMeta: metav1.ObjectMeta{Name: "mysvc", Namespace: "namespace"},
			},
		},
		"no name required for singleton port": {
			endpoints: core.Endpoints{
				ObjectMeta: metav1.ObjectMeta{Name: "mysvc", Namespace: "namespace"},
				Subsets: []core.EndpointSubset{{

                  type: string
                type: array
              host:
                description: The name of a service from the service registry.
                type: string
              subsets:
                description: One or more named sets that represent individual versions
                  of a service.
                items:
                  properties:
                    labels:

                  type: string
                type: array
              host:
                description: The name of a service from the service registry.
                type: string
              subsets:
                description: One or more named sets that represent individual versions
                  of a service.
                items:
                  properties:
                    labels:

                  type: string
                type: array
              host:
                description: The name of a service from the service registry.
                type: string
              subsets:
                description: One or more named sets that represent individual versions
                  of a service.
                items:
                  properties:
                    labels:

    Building signatures from these allows TF Serving to honor requests using the
    different APIs (Classify, Regress, and Predict). Furthermore,
    `serving_input_receiver_fn()` may now specify alternative subsets of nodes
    that may act as inputs. This allows, for instance, producing a prediction
    signature for a classifier that accepts raw `Tensors` instead of a
    serialized `tf.Example`.