`DynamicLossScale` will no longer affect the weights of the
        LossScaleOptimizer, and vice versa.
    *   The global policy can no longer be set to a non-floating point policy in
        `tf.keras.mixed_precision.experimental.set_policy`
    *   In `Layer.call`, `AutoCastVariable`s will no longer be casted within

            "type": "string"
          },
          "selfLink": {
            "description": "Deprecated: selfLink is a legacy read-only field that is no longer populated by the system.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "io.k8s.apimachinery.pkg.apis.meta.v1.ManagedFieldsEntry": {

  - `servicePort` -> `service.port.number` (for numeric values)
  - `pathType` no longer has a default value in v1; "Exact", "Prefix", or "ImplementationSpecific" must be specified

  Other Ingress API updates:
  - backends can now be resource or service backends

            "format": "int64",
            "type": "integer"
          },
          "tolerations": {

                            to complete.


                            Setting a timeout to the zero duration (e.g. "0s") SHOULD disable the timeout
                            completely. Implementations that cannot completely disable the timeout MUST
                            instead interpret the zero duration as the longest possible value to which

the third with molten Pitch, and the Liquors be stirred about alike to
give them a vortical Motion; the Pitch by its Tenacity will lose its
Motion quickly, the Oil being less tenacious will keep it longer, and
the Water being less tenacious will keep it longest, but yet will lose
it in a short time. Whence it is easy to understand, that if many
contiguous Vortices of molten Pitch were each of them as large as those

							LocalhostProfile: ptr.To("foo-bar "),
						},
					},
				},
			},
		},
		"too long AppArmor localhost profile": {
			expectedError: "Too long: may not be longer than 4095",
			spec: core.Pod{
				ObjectMeta: metav1.ObjectMeta{
					Name:      "123",
					Namespace: "ns",
				},
				Spec: core.PodSpec{

Otherwise, it has `r+1` dimensions `[I, J, ..., L, num_diags, max_diag_len]`.
`num_diags` is the number of diagonals, `num_diags = k[1] - k[0] + 1`.
`max_diag_len` is the longest diagonal in the range `[k[0], k[1]]`,
`max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))`

The output is a tensor of rank `k+1` with dimensions `[I, J, ..., L, M, N]`.
If `k` is scalar or `k[0] == k[1]`:

		{"(*Regexp).FindStringSubmatchIndex", Method, 0},
		{"(*Regexp).FindSubmatch", Method, 0},
		{"(*Regexp).FindSubmatchIndex", Method, 0},
		{"(*Regexp).LiteralPrefix", Method, 0},
		{"(*Regexp).Longest", Method, 1},
		{"(*Regexp).MarshalText", Method, 21},
		{"(*Regexp).Match", Method, 0},
		{"(*Regexp).MatchReader", Method, 0},
		{"(*Regexp).MatchString", Method, 0},
		{"(*Regexp).NumSubexp", Method, 0},