Struct Linear 

pub struct Linear {
    pub weights: Tensor,
    pub biases: Tensor,
    pub activation: Activations,
    /* private fields */
}

A 2D linearly densely-connected layer

Fields

weights: Tensor

biases: Tensor

activation: Activations

Implementations

impl Linear

pub fn new( input_dim: usize, output_dim: usize, activation: Activations, ) -> Linear

Create a new linear layer

Examples found in repository

examples/nn_full.rs (line 11)

fn main() {
    Logger::new().init().unwrap();
    let x = Tensor::linspace(-5.0, 5.0, 50);
    let func = &x * -5.0;
    let y = &func + &(Tensor::rand([50, 1]) * 0.4);

    let mut model = Model::new();
    model.add_layer(Linear::new(1, 10, Activations::None));
    model.add_layer(Linear::new(10, 10, Activations::None));
    model.add_layer(Linear::new(10, 1, Activations::None));

    model.compile(Optimizers::SGD);
    model.fit(&x, &y, 500, 0.00001, true);

    let x_pred = scalar!(1.0);
    let y_pred = model.predict(&x_pred);
    println!("Predict result (should be -5): {:?}", y_pred);
}

Trait Implementations

impl Layer for Linear

fn parameters(&self) -> Vec<&Tensor>

fn forward(&self, train_data: &Tensor) -> Tensor

fn shape(&self) -> (usize, usize)

fn zero_grad(&self)