if you see such issues, please use the legacy optimizer, and file
        an issue in the Keras GitHub repo.

    The old Keras optimizer will never be deleted, but will not see any
    new feature additions.
    New optimizers (e.g., `Adafactor`) will
    only be implemented based on `tf.keras.optimizers.Optimizer`, the new
    base class.

## Changes by Kind

### Bug or Regression

- Fix race condition in scheduler where a new unschedulable Pod might never be retried. ([#105015](https://github.com/kubernetes/kubernetes/pull/105015), [@alculquicondor](https://github.com/alculquicondor)) [SIG Apps, Scheduling and Testing]
- Fix: skip case sensitivity when checking Azure NSG rules

final cipher Ldec_tail: // Cipher last two keys such that key information is // cleared from V1 and V2. VCIPHER V0, V1, V1 VCIPHERLAST V1, V2, V2 // Store the result in BE order. P8_STXVB16X(V2, R3, R0) RET Linvalid_key_len: // Segfault, this should never happen. Only 3 keys sizes are created/used. MOVD R0, 0(R0) RET // func decryptBlockAsm(nr int, xk *uint32, dst, src *byte) TEXT ·decryptBlockAsm(SB), NOSPLIT|NOFRAME, $0 MOVD nr+0(FP), R6 // Round count/Key size MOVD xk+8(FP), R5 // Key pointer MOVD...

    * PR [#1862](https://github.com/tiangolo/fastapi/pull/1862).
* In `encoders.jsonable_encoder` remove parameter `sqlalchemy_safe`.
    * It was an early hack to allow returning SQLAlchemy models, but it was never documented, and the recommended way is using Pydantic's `orm_mode` as described in the tutorial: [SQL (Relational) Databases](https://fastapi.tiangolo.com/tutorial/sql-databases/).