* [Microservice in Python using FastAPI](https://dev.to/paurakhsharma/microservice-in-python-using-fastapi-24cc)  by [Paurakh Sharma Humagain](https://x.com/PaurakhSharma).
        * [Build simple API service with Python FastAPI — Part 1](https://dev.to/cuongld2/build-simple-api-service-with-python-fastapi-part-1-581o) by [cuongld2](https://dev.to/cuongld2).

        -  The API may be available in the public Keras API under a different name, so make sure to look for it on keras.io or TensorFlow docs and switch to the public version.
        -  It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own!
        -  If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.

     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getPasswordInvalidAdminPasswords();

    /**
     * The simple implementation for configuration.
     * @author FreeGen
     */
    public static class SimpleImpl extends FessEnv.SimpleImpl implements FessConfig {

func (out *Nat) ExpShortVarTime(x *Nat, e uint, m *Modulus) *Nat { if !m.odd { panic("bigmod: modulus for ExpShortVarTime must be odd") } // For short exponents, precomputing a table and using a window like in Exp // doesn't pay off. Instead, we do a simple conditional square-and-multiply // chain, skipping the initial run of zeroes. xR := NewNat().set(x).montgomeryRepresenta(m) out.set(xR) for i := bits.UintSize - bits.Len(e) + 1; i < bits.UintSize; i++ { out.montgomeryMul(out, out, m) if k := (e >>...