*   Added warmup capabilities to `tf.keras.optimizers.schedules.CosineDecay` learning rate scheduler. You can now specify an initial and target learning rate, and our scheduler will perform a linear interpolation between the two after which it will begin a decay phase.

</div>

Note that on CPU, if an out of bound index is found, an error is returned.
On GPU, if an out of bound index is found, a 0 is stored in the
corresponding output value.

Note that on TPU, if any dimension of `params` is of size 0 then the output will
be the expected shape filled with zeros. On CPU and GPU an error will be
returned.

See also `tf.batch_gather` and `tf.gather_nd`.

              }
            ],

                          description: An optional list of hex-encoded SHA-256 hashes
                            of the authorized client certificates.
                          items:
                            type: string
                          type: array
                        verifyCertificateSpki:
                          description: An optional list of base64-encoded SHA-256

                          description: An optional list of hex-encoded SHA-256 hashes
                            of the authorized client certificates.
                          items:
                            type: string
                          type: array
                        verifyCertificateSpki:
                          description: An optional list of base64-encoded SHA-256

				EphemeralContainers: ephemeralContainers,
				RestartPolicy:       core.RestartPolicyOnFailure,
			},
		}
	}

	// Some tests use Windows host pods as an example of fields that might
	// conflict between an ephemeral container and the rest of the pod.
	capabilities.SetForTests(capabilities.Capabilities{
		AllowPrivileged: true,
	})