Enum Optimizer 

pub enum Optimizer {
    GradientDescent {
        learning_rate: f64,
    },
    Adam {
        learning_rate: f64,
        beta1: f64,
        beta2: f64,
        epsilon: f64,
    },
    SPSA {
        learning_rate: f64,
        perturbation: f64,
    },
    SciRS2 {
        method: String,
        config: HashMap<String, f64>,
    },
}

Optimizer for quantum machine learning models

Variants

GradientDescent

Gradient descent

Fields

learning_rate: f64

Learning rate

Adam

Adam optimizer

Fields

learning_rate: f64

Learning rate

beta1: f64

Beta1 parameter

beta2: f64

Beta2 parameter

epsilon: f64

Epsilon parameter

SPSA

SPSA optimizer

Fields

learning_rate: f64

Learning rate

perturbation: f64

Perturbation size

SciRS2

SciRS2-based optimizers (placeholder for integration)

Fields

method: String

Optimizer method

config: HashMap<String, f64>

Configuration parameters

Implementations

impl Optimizer

pub fn new(method: OptimizationMethod) -> Self

Creates a new optimizer with default parameters

pub fn update_parameters( &self, parameters: &mut Array1<f64>, gradients: &ArrayView1<'_, f64>, iteration: usize, ) -> Result<()>

Updates parameters based on gradients

Trait Implementations

impl Clone for Optimizer

fn clone(&self) -> Optimizer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Optimizer

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

Formats the value using the given formatter.

impl Display for Optimizer

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

Formats the value using the given formatter.