scenarios := map[string]struct {
		isExpectedFailure           bool
		enableVolumeAttributesClass bool
		volume                      *core.PersistentVolume
	}{
		"good-volume": {
			isExpectedFailure: false,
			volume: testVolume("foo", "", core.PersistentVolumeSpec{
				Capacity: core.ResourceList{
					core.ResourceName(core.ResourceStorage): resource.MustParse("10G"),
				},

322A          ; disallowed_STD3_mapped ; 0028 6708 0029 #1.1  PARENTHESIZED IDEOGRAPH MOON
322B          ; disallowed_STD3_mapped ; 0028 706B 0029 #1.1  PARENTHESIZED IDEOGRAPH FIRE
322C          ; disallowed_STD3_mapped ; 0028 6C34 0029 #1.1  PARENTHESIZED IDEOGRAPH WATER
322D          ; disallowed_STD3_mapped ; 0028 6728 0029 #1.1  PARENTHESIZED IDEOGRAPH WOOD
322E          ; disallowed_STD3_mapped ; 0028 91D1 0029 #1.1  PARENTHESIZED IDEOGRAPH METAL

    which is a NumPy-compatible API for writing TF programs. This module
    provides class `ndarray`, which mimics the `ndarray` class in NumPy, and
    wraps an immutable `tf.Tensor` under the hood. A subset of NumPy functions
    (e.g. `numpy.add`) are provided. Their inter-operation with TF facilities is
    seamless in most cases. See

                    useful object to place Policy status on, so we recommend that implementations
                    SHOULD use Gateway as the PolicyAncestorStatus object unless the designers
                    have a _very_ good reason otherwise.


                    In the context of policy attachment, the Ancestor is used to distinguish which
                    resource results in a distinct application of this policy. For example, if a policy

the concatenation, will use the values of the captured tensors available to it.
Therefore, typical uses of captured tensors should involve values which remain
unchanged across session.run calls. Inference is a good example of this.

SparseTensor is not supported. The return value of the decorated function
must be a Tensor or a list/tuple of Tensors.
  }];

  let arguments = (ins