Support computing of partial derivatives about burn

[nathanielsimard]

I'm unsure I understand the concept of mixed partial derivatives, but it would be nice if burn could satisfy your use case.

The Gradients struct provides a way of getting partial derivates, though the API might be improved. From the concrete type in burn-autodiff you can do something like this:

fn run<B: Backend>() {
    let a = ADTensor::<B, 2>::random(...);
    let b = ADTensor::<B, 2>::random(...);
    let y = some_function(&a, &b);
    
    let grads = y.backward();
    
    let grad_a = grads.wrt(&a); // d some_function / da
    let grad_b = grads.wrt(&b); // d some_function / db
}

[antimora]

I am closing this because for now we do not have more information and specifics about the feature request. Please feel to reopen if more information is provided.