return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_EmptyOp : TF_Op<"Empty", []> {
  let summary = [{
Creates a tensor with the given shape.

This operation creates a tensor of `shape` and `dtype`.
  }];

  let arguments = (ins
    Arg<TF_Int32Tensor, [{1-D. Represents the shape of the output tensor.}]>:$shape,

    *   Graduated experimental APIs:
        *   [`tf.data.Dataset.counter`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#counter),
            which creates `Dataset`s of indefinite sequences of numbers.
        *   [`tf.data.Dataset.ignore_errors`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ignore_errors),
            which drops erroneous elements from `Dataset`s.

                                    description: |-
                                      A label selector requirement is a selector that contains values, a key, and an operator that
                                      relates the key and values.
                                    properties:
                                      key:
                                        description: key is the label key that the

        "x-kubernetes-map-type": "atomic"
      },
      "io.k8s.api.core.v1.NodeSelectorRequirement": {
        "description": "A node selector requirement is a selector that contains values, a key, and an operator that relates the key and values.",
        "properties": {
          "key": {
            "default": "",
            "description": "The label key that the selector applies to.",
            "type": "string"
          },

        "x-kubernetes-map-type": "atomic"
      },
      "io.k8s.api.core.v1.NodeSelectorRequirement": {
        "description": "A node selector requirement is a selector that contains values, a key, and an operator that relates the key and values.",
        "properties": {
          "key": {
            "default": "",
            "description": "The label key that the selector applies to.",
            "type": "string"
          },

		if errs := validateOverhead(tc.overhead, field.NewPath("resources"), PodValidationOptions{}); len(errs) == 0 {
			t.Errorf("%q expected error", tc.Name)
		}
	}
}

// helper creates a pod with name, namespace and IPs
func makePod(podName string, podNamespace string, podIPs []core.PodIP) core.Pod {
	return core.Pod{
		ObjectMeta: metav1.ObjectMeta{Name: podName, Namespace: podNamespace},