Struct OptimizationProblem 

pub struct OptimizationProblem<F: Float + Debug> {
    pub initial_params: Array1<F>,
    pub target: Array1<F>,
    pub max_steps: usize,
}

Optimization problem for meta-optimizer training

Fields

initial_params: Array1<F>

Initial parameters

target: Array1<F>

Target parameters

max_steps: usize

Maximum optimization steps

Implementations

impl<F: Float + Debug> OptimizationProblem<F>

pub fn new( initial_params: Array1<F>, target: Array1<F>, max_steps: usize, ) -> Self

Create a new optimization problem

pub fn quadratic(dim: usize, max_steps: usize) -> Self

where F: FromPrimitive,

Create a quadratic optimization problem

pub fn random(dim: usize, max_steps: usize) -> Self

where F: FromPrimitive,

Create a random optimization problem

pub fn dimension(&self) -> usize

Get the dimension of the problem

pub fn evaluate(&self, params: &Array1<F>) -> F

Evaluate the objective function at given parameters

pub fn gradient(&self, params: &Array1<F>) -> Array1<F>

Compute the gradient at given parameters

pub fn has_converged(&self, params: &Array1<F>, tolerance: F) -> bool

Check if the problem has converged

Trait Implementations

impl<F: Clone + Float + Debug> Clone for OptimizationProblem<F>

fn clone(&self) -> OptimizationProblem<F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug + Float + Debug> Debug for OptimizationProblem<F>

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

Formats the value using the given formatter.