}
            ],
            "default": {},
            "description": "Spec describes the desired attributes of a resource that then needs to be allocated. It can only be set once when creating the ResourceClaim."
          },
          "status": {
            "allOf": [
              {
                "$ref": "#/components/schemas/io.k8s.api.resource.v1alpha2.ResourceClaimStatus"
              }

      priority: 1
      type: string
    name: v1
    schema:
      openAPIV3Schema:
        description: |-
          GatewayClass describes a class of Gateways available to the user for creating
          Gateway resources.


          It is recommended that this resource be used as a template for Gateways. This
          means that a Gateway is based on the state of the GatewayClass at the time it

        CPU/memory usage.
    *   Added
        [`tf.data.experimental.from_list`](https://www.tensorflow.org/api_docs/python/tf/data/experimental/from_list),
        a new API for creating `Dataset`s from lists of elements.
    *   Graduated experimental APIs:
        *   [`tf.data.Dataset.counter`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#counter),

            "type": "string"
          }
        },
        "type": "object"
      },
      "io.k8s.api.core.v1.ClusterTrustBundleProjection": {

pipelines to be defined without an additional initialization
("MakeIterator") step.

One-shot iterators have the following limitations:

* They do not support parameterization: all logic for creating the underlying
  dataset must be bundled in the `dataset_factory` function.
* They are not resettable. Once a one-shot iterator reaches the end of its
  underlying dataset, subsequent "IteratorGetNext" operations on that