"type": "string"
          },
          "path": {
            "default": "",
            "description": "path is the Glusterfs volume path. More info: https://examples.k8s.io/volumes/glusterfs/README.md#create-a-pod",
            "type": "string"
          },
          "readOnly": {

*  The default Keras model saving format is now the Keras v3 format: calling `model.save("xyz.keras")` will no longer create a H5 file, it will create a native Keras model file. This will only be breaking for you if you were manually inspecting or modifying H5 files saved by Keras under a `.keras` extension. If this breaks you, simply add `save_format="h5"` to your `.save()` call to...

            "type": "string"
          },
          "verbs": {
            "description": "verbs is a list of supported kube verbs (this includes get, list, watch, create, update, patch, delete, deletecollection, and proxy)",
            "items": {
              "default": "",
              "type": "string"
            },
            "type": "array"
          },

		testName     string
		claimSpec    core.PersistentVolumeClaimSpec
		expectedFail bool
	}{{
		testName:  "test create from valid snapshot source",
		claimSpec: *testDataSourceInSpec("test_snapshot", "VolumeSnapshot", "snapshot.storage.k8s.io"),
	}, {
		testName:  "test create from valid pvc source",
		claimSpec: *testDataSourceInSpec("test_pvc", "PersistentVolumeClaim", ""),
	}, {

                  and allow "consumer" routes for the referenced Service. ReferenceGrant is
                  not applicable for governing ParentRefs to Services - it is not possible to
                  create a "producer" route for a Service in a different namespace from the
                  Route.


                  There are two kinds of parent resources with "Core" support:

     For example, in the equation `iii->i` with input shape `[3, 3, 3]`, the
     generalized diagonal would consist of `3` elements at indices `(0, 0, 0)`,
     `(1, 1, 1)` and `(2, 2, 2)` to create a Tensor of shape `[3]`.

 (b) Reduction: Axes corresponding to labels appearing only in one input
     subscript but not in the output subscript are summed over prior to Tensor
     contraction.