*   `tf.raw_ops.Bucketize` op on CPU.
        *   `tf.where` op for data types
            `tf.int32`/`tf.uint32`/`tf.int8`/`tf.uint8`/`tf.int64`.
        *   `tf.random.normal` op for output data type `tf.float32` on CPU.
        *   `tf.random.uniform` op for output data type `tf.float32` on CPU.
        *   `tf.random.categorical` op for output data type `tf.int64` on CPU.

*   `tensorflow.experimental.tensorrt`:

gcmAesFinish(productTable *[256]byte, tagMask, T *[16]byte, pLen, dLen uint64) // Keep in sync with crypto/tls.hasAESGCMHardwareSup. var supportsAESGCM = cpu.X86HasAES && cpu.X86HasPCLMULQDQ && cpu.X86HasSSE41 && cpu.X86HasSSSE3 || cpu.ARM64HasAES && cpu.ARM64HasPMULL func init() { if cpu.AMD64 { impl.Register("gcm", "AES-NI", &supportsAESGCM) } if cpu.ARM64 { impl.Register("gcm", "Armv8.0", &supportsAESGCM) } } // checkGenericIsExpect is called by the variable-time implementation to make // sure it...

- Using NUMA nodes instead of sockets for CPU manager hints. ([#99276](https://github.com/kubernetes/kubernetes/pull/99276), [@iwankgb](https://github.com/iwankgb)) [SIG Node]

     */
    String getCrawlerHotthreadTimeout();

    /**
     * Get the value for the key 'crawler.hotthread.type'. <br>
     * The value is, e.g. cpu <br>
     * comment: Type of hot thread monitoring (e.g., cpu).
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getCrawlerHotthreadType();

    /**

    * This solves a vulnerability that could allow denial of service attacks by using many small multipart fields/files (parts), consuming high CPU and memory.
    * Only applications using forms (e.g. file uploads) could be affected.
    * For most cases, upgrading won't have any breaking changes.

## 0.91.0

### Upgrades