String getAppCipherAlgorism();

    /**
     * Get the value for the key 'app.cipher.key'. <br>
     * The value is, e.g. ___change__me___ <br>
     * comment: Secret key for encryption (change this value for production).
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getAppCipherKey();

    /**

    - [Ingress graduates to General Availability](#ingress-graduates-to-general-availability)
    - [seccomp graduates to General Availability](#seccomp-graduates-to-general-availability)
    - [Production images moved to community control](#production-images-moved-to-community-control)
    - [KubeSchedulerConfiguration graduates to Beta](#kubeschedulerconfiguration-graduates-to-beta)

    *   New loss reduction types:
    *   `AUTO`: Indicates that the reduction option will be determined by the
        usage context. For almost all cases this defaults to
        `SUM_OVER_BATCH_SIZE`. When used with `tf.distribute.Strategy`, outside
        of built-in training loops such as `tf.keras` `compile` and `fit`, we
        expect reduction value to be `SUM` or `NONE`. Using `AUTO` in that case

 │                                                     │
 │  API docs: http://127.0.0.1:8000/docs               │
 │                                                     │
 │  Running in development mode, for production use:   │
 │                                                     │
 │  fastapi run                                        │
 │                                                     │

IN1, H2H, XH1 // H^2.hi·H^2.hi VPMSUMD XL, XC2, T2 // 1st reduction phase VPMSUMD XL1, XC2, HH // 1st reduction phase VSLDOI $8, XM, ZERO, T0 VSLDOI $8, ZERO, XM, T1 VSLDOI $8, XM1, ZERO, HL VSLDOI $8, ZERO, XM1, H VXOR XL, T0, XL VXOR XH, T1, XH VXOR XL1, HL, XL1 VXOR XH1, H, XH1 VSLDOI $8, XL, XL, XL VSLDOI $8, XL1, XL1, XL1 VXOR XL, T2, XL VXOR XL1, HH, XL1 VSLDOI $8, XL, XL, T1 // 2nd reduction phase VSLDOI $8, XL1, XL1, H // 2nd reduction phase VPMSUMD XL, XC2, XL VPMSUMD XL1, XC2, XL1 VXOR T1,...