A set of common keys MAY be defined by the API in the future. To avoid
                            any ambiguity, implementation-specific definitions MUST use
                            domain-prefixed names, such as `example.com/my-custom-option`.
                            Un-prefixed names are reserved for key names defined by Gateway API.

            },

        "properties": {
          "causes": {

(K-1)-dimensional tensor of indices into `params`, where each element defines a
slice of `params`:

    output[\\(i_0, ..., i_{K-2}\\)] = params[indices[\\(i_0, ..., i_{K-2}\\)]]

Whereas in `tf.gather` `indices` defines slices into the `axis`
dimension of `params`, in `tf.gather_nd`, `indices` defines slices into the
first `N` dimensions of `params`, where `N = indices.shape[-1]`.

									}},
								},
								Namespaces: []string{"ns"},
							},
						}},
					},
				}),
			},
		},
		"invalid soft pod affinity, key in MatchLabelKeys isn't correctly defined": {
			expectedError: "prefix part must be non-empty",
			spec: core.Pod{
				ObjectMeta: metav1.ObjectMeta{
					Name:      "123",
					Namespace: "ns",
				},

                      type: object
                  type: object
                type: array
              priority:
                description: Priority defines the order in which patch sets are applied
                  within a context.
                format: int32
                type: integer
              targetRefs:
                description: Optional.

                      type: object
                  type: object
                type: array
              priority:
                description: Priority defines the order in which patch sets are applied
                  within a context.
                format: int32
                type: integer
              targetRefs:
                description: Optional.

Circle, illuminated with homogeneal Light, appeared circular and
distinctly defined, as when 'tis view'd with the naked Eye. Which proves
the whole Proposition.

_Exper._ 14. In the homogeneal Light I placed Flies, and such-like
minute Objects, and viewing them through a Prism, I saw their Parts as
distinctly defined, as if I had viewed them with the naked Eye. The same

            compatibility with GPU delegate.

*   Extension Types

    *   Add experimental API to define new Python classes that can be handled by
        TensorFlow APIs. To create an extension type, simply define a Python
        class with `tf.experimental.ExtensionType` as its base, and use type
        annotations to specify the type for each field. E.g.: `python class

                      type: object
                  type: object
                type: array
              priority:
                description: Priority defines the order in which patch sets are applied
                  within a context.
                format: int32
                type: integer
              workloadSelector: