I would like tensorflow team to contribute on my project, update it and add it to its library in rust

It’s super speed than python, suitable for all devices including embedded and low level devices

The example you see is just using Linear activation function, you can also try relu, sigmoid or tanh, the softmax is not implemented yet

Take a look

```
use rkl::prelude::*;
fn main() {
let x = array![[1., 2.], [3., 4.], [5., 6.]];
let y = array![[3.], [7.], [11.]];
let mut model = Sequential::new(&[
Dense::new(4, 2, Activation::Linear),
Dense::new(2, 4, Activation::Linear),
Dense::new(1, 2, Activation::Linear),
]);
model.summary();
model.compile(Optimizer::SGD(0.01), Loss::MSE);
model.fit(x, y, 1000, true);
let x_test = array![[2., 3.]];
let y_test = array![[5.]];
let eval = model.evaluate(x_test.clone(), y_test);
println!("\ncost: {}\n", eval);
let prediction = model.predict(x_test);
println!("prediction: {}", prediction);
model.save("./test.model");
}
```