Struct Optimizer 

pub struct Optimizer<T> {
    pub loss: Box<dyn Loss<T>>,
    pub network: Network,
    pub max_gradient: Option<f64>,
}

Fields

loss: Box<dyn Loss<T>>

network: Network

max_gradient: Option<f64>

Implementations

impl<T: Clone> Optimizer<T>

pub fn apply(&mut self, input: &Array1<f64>, target: &T) -> (Array1<f64>, f64)

Apply the network to an input and update gradients, returning the output and loss as a tuple

pub fn step(&mut self, learning_rate: f64)

Update weights and zero the gradients