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* The implicit registration of Prometheus metrics for workqueue has been removed, and a plug-able interface was added. If you were using workqueue in your own binaries and want these metrics, add the following to your imports in the main package: "k8s.io/pkg/util/workqueue/prometheus". ([#33792](https://github.com/kubernetes/kubernetes/pull/33792),...

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x3lo, x3hi := mul51(x.l3, y) x4lo, x4hi := mul51(x.l4, y) v.l0 = x0lo + 19*x4hi // carried over per the reduction identity v.l1 = x1lo + x0hi v.l2 = x2lo + x1hi v.l3 = x3lo + x2hi v.l4 = x4lo + x3hi // The hi portions are going to be only 32 bits, plus any previous excess, // so we can skip the carry propagation. return v } // mul51 returns lo + hi * 2⁵¹ = a * b. func mul51(a uint64, b uint32) (lo uint64, hi uint64) { mh, ml := bits.Mul64(a, uint64(b)) lo = ml & maskLow51Bits hi = (mh << 13) | (ml...

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        gathered at runtime to be used in embedding layer partitioning
        decisions.
*   PluggableDevice
    *   Third-party devices can now connect to TensorFlow as plug-ins through
        [StreamExecutor C API](https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md).
        and