*   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.

	RDSEEDQ R11                             // 490fc7fb
	RDTSC                                   // 0f31
	RDTSCP                                  // 0f01f9
	JCS 2(PC)
	//TODO: RETQ                            // c3
	JCS 2(PC)
	//TODO: RETQ $0xf123                    // c223f1
	JCS 2(PC)
	//TODO: RETFQ                           // cb
	JCS 2(PC)
	//TODO: RETFQ $0xf123                   // ca23f1

                        - name
                        type: object
                      type: array
                    randomSamplingPercentage:
                      description: Controls the rate at which traffic will be selected
                        for tracing if no prior sampling decision has been made.
                      format: double
                      maximum: 100

- Openapi-controller: remove the trailing `1` character literal from the rate limiting metric `APIServiceOpenAPIAggregationControllerQueue1` and rename it to `open_api_aggregation_controller` to adhere to Prometheus best practices. ([#77979](https://github.com/kubernetes/kubernetes/pull/77979), [@s-urbaniak](https://github.com/s-urbaniak))...