Struct LinearModel 

pub struct LinearModel { /* private fields */ }

A simple linear model for testing and demonstration.

Implementations

impl LinearModel

pub fn new(input_dim: usize, output_dim: usize) -> Self

Create a new linear model.

Arguments

• input_dim - Input dimension
• output_dim - Output dimension

pub fn xavier_init(&mut self)

Initialize parameters with Xavier/Glorot uniform initialization.

pub fn input_dim(&self) -> usize

Get input dimension.

pub fn output_dim(&self) -> usize

Get output dimension.

Trait Implementations

impl Clone for LinearModel

fn clone(&self) -> LinearModel

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for LinearModel

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Model for LinearModel

fn forward( &self, input: &ArrayView<'_, f64, Ix2>, ) -> TrainResult<Array<f64, Ix2>>

Perform a forward pass through the model.

fn backward( &self, input: &ArrayView<'_, f64, Ix2>, grad_output: &ArrayView<'_, f64, Ix2>, ) -> TrainResult<HashMap<String, Array<f64, Ix2>>>

Perform a backward pass to compute gradients.

fn parameters(&self) -> &HashMap<String, Array<f64, Ix2>>

Get a reference to the model’s parameters.

fn parameters_mut(&mut self) -> &mut HashMap<String, Array<f64, Ix2>>

Get a mutable reference to the model’s parameters.

fn set_parameters(&mut self, parameters: HashMap<String, Array<f64, Ix2>>)

Set the model’s parameters.

fn reset_parameters(&mut self)

Reset model parameters (optional, for retraining).

fn num_parameters(&self) -> usize

Get the number of parameters in the model.

fn state_dict(&self) -> HashMap<String, Vec<f64>>

Save model state to a dictionary.

fn load_state_dict( &mut self, state: HashMap<String, Vec<f64>>, ) -> TrainResult<()>

Load model state from a dictionary.