*   Raw TensorFlow functions can now be used in conjunction with the Keras
        Functional API during model creation. This obviates the need for users
        to create Lambda layers in most cases when using the Functional API.
        Like Lambda layers, TensorFlow functions that result in Variable
        creation or assign ops are not supported.
    *   Add support for passing list of lists to the `metrics` argument in Keras

`0.24.0`, a new instance of each middleware class would be created when a new middleware was added. That normally was not a problem, unless the middleware class expected to be created only once, with only one instance, that happened in some cases. This upgrade would solve those cases (thanks [@adriangb](https://github.com/adriangb)! Starlette PR [#2017](https://github.com/encode/starlette/pull/2017)). Now the middleware class instances are created once, right before the first request (the first time the...

96. y := x for i := 0; i < 5; i++ { y = y * (2 - x*y) } return -y } // NewModulus creates a new Modulus from a slice of big-endian bytes. The // modulus must be greater than one. // // The number of significant bits and whether the modulus is even is leaked // through timing side-channels. func NewModulus(b []byte) (*Modulus, error) { n := NewNat().resetToBytes(b) return newModulus(n) } // NewModulusProduct creates a new Modulus from the product of two numbers // represented as big-endian byte slices....