Struct neural_network_rs::neural_network::Network

pub struct Network<'a> {
    pub layers: Vec<Layer<'a>>,
    pub shape: &'a [(&'a ActivationFunction, usize)],
    pub cost_function: &'a CostFunction,
    /* private fields */
}

Fields

layers: Vec<Layer<'a>>

shape: &'a [(&'a ActivationFunction, usize)]

cost_function: &'a CostFunction

Implementations

impl Network<'_>

pub fn new<'a>(
    shape: &'a [(&ActivationFunction, usize)],
    optimizer: &'a mut dyn Optimizer,
    cost_function: &'a CostFunction
) -> Network<'a>

pub fn predict(&self, input: &Array2<f64>) -> Array2<f64>

pub fn backprop(
    &self,
    X: &Array2<f64>,
    y: &Array2<f64>
) -> (Vec<Array2<f64>>, Vec<Array2<f64>>)

pub fn train_minibatch(&mut self, (X, y): &(Array2<f64>, Array2<f64>))

pub fn train_and_log(
    &mut self,
    data: &Dataset<'_>,
    batch_size: usize,
    verification_samples: usize,
    epochs: i32
) -> Vec<(i32, f64)>

pub fn eval(&self, data: &Dataset<'_>, sample_size: usize) -> f64

pub fn predict_unit_square(
    &self,
    resolution: usize
) -> ((usize, usize), Vec<Vec<f64>>)

Trait Implementations

impl Summary for Network<'_>

fn summerize(&self) -> String