Trait Model 

pub trait Model {
    // Required methods
    fn forward(
        &self,
        input: &ArrayView<'_, f64, Ix2>,
    ) -> TrainResult<Array<f64, Ix2>>;
    fn backward(
        &self,
        input: &ArrayView<'_, f64, Ix2>,
        grad_output: &ArrayView<'_, f64, Ix2>,
    ) -> TrainResult<HashMap<String, Array<f64, Ix2>>>;
    fn parameters(&self) -> &HashMap<String, Array<f64, Ix2>>;
    fn parameters_mut(&mut self) -> &mut HashMap<String, Array<f64, Ix2>>;
    fn set_parameters(&mut self, parameters: HashMap<String, Array<f64, Ix2>>);

    // Provided methods
    fn num_parameters(&self) -> usize { ... }
    fn state_dict(&self) -> HashMap<String, Vec<f64>> { ... }
    fn load_state_dict(
        &mut self,
        state: HashMap<String, Vec<f64>>,
    ) -> TrainResult<()> { ... }
    fn reset_parameters(&mut self) { ... }
}

Trait for trainable models.

This trait defines the interface for models that can be trained with the Tensorlogic training infrastructure. Models must implement forward and backward passes, parameter management, and optional save/load functionality.

Required Methods

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

Perform a forward pass through the model.

Arguments

• input - Input tensor

Returns

Output tensor from 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.

Arguments

• input - Input tensor used in forward pass
• grad_output - Gradient of loss with respect to model output

Returns

Gradients for each model parameter

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.

Provided Methods

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.

fn reset_parameters(&mut self)

Reset model parameters (optional, for retraining).

Implementors

impl Model for LinearModel