Struct SOFOConfig 

pub struct SOFOConfig {

    pub learning_rate: f32,
    pub batch_size: usize,
    pub forward_passes: usize,
    pub curvature_strength: f32,
    pub damping: f32,
    pub weight_decay: f32,
    pub adaptive_curvature: bool,
    pub momentum: f32,
    pub nesterov: bool,
    pub max_condition_number: f32,
    pub memory_efficient: bool,
    pub parallel_threshold: usize,
    pub hvp_epsilon: f32,
    pub probe_seed: u64,
}

Configuration for SOFO optimizer

Fields

learning_rate: f32

Learning rate (default: 1e-3)

batch_size: usize

Batch size for forward-mode differentiation (default: 32)

forward_passes: usize

Number of forward passes for curvature estimation (default: 8)

curvature_strength: f32

Strength of curvature information (default: 0.1)

damping: f32

Damping factor for numerical stability (default: 1e-6)

weight_decay: f32

Weight decay (default: 0.0)

adaptive_curvature: bool

Enable adaptive curvature estimation (default: true)

momentum: f32

Momentum for first-order updates (default: 0.9)

nesterov: bool

Use Nesterov acceleration (default: true)

max_condition_number: f32

Maximum condition number for curvature matrix (default: 1e6)

memory_efficient: bool

Enable memory efficient mode (default: true)

parallel_threshold: usize

Parallel computation threshold (default: 1000)

hvp_epsilon: f32

Finite-difference step used for the Hessian-vector product (default: 1e-3).

A central difference of gradients trades truncation error (O(ε²)) against cancellation error (O(δ/ε) for gradient noise δ); 1e-3 is the usual compromise for f32 parameters.

probe_seed: u64

Seed for the Rademacher probe stream (default: 0x5060_F0F0_1234_5678).

Implementations

impl SOFOConfig

pub fn new() -> Self

Create a new SOFO configuration with default values

pub fn learning_rate(self, lr: f32) -> Self

Set the learning rate

pub fn batch_size(self, batch_size: usize) -> Self

Set the batch size for forward-mode differentiation

pub fn forward_passes(self, passes: usize) -> Self

Set the number of forward passes for curvature estimation

pub fn curvature_strength(self, strength: f32) -> Self

Set the curvature strength

pub fn damping(self, damping: f32) -> Self

Set the damping factor

pub fn weight_decay(self, decay: f32) -> Self

Set weight decay

pub fn momentum(self, momentum: f32) -> Self

Enable or disable momentum

pub fn hvp_epsilon(self, eps: f32) -> Self

Set the finite-difference step for the Hessian-vector product.

pub fn probe_seed(self, seed: u64) -> Self

Set the seed of the Rademacher probe stream.

pub fn adaptive_curvature(self, enable: bool) -> Self

Build the configuration Enable or disable adaptive per-parameter curvature weighting

pub fn max_condition_number(self, max_condition_number: f32) -> Self

Set the maximum condition number tolerated in the curvature estimate

pub fn build(self) -> Self

Trait Implementations

impl Clone for SOFOConfig

fn clone(&self) -> SOFOConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SOFOConfig

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

Formats the value using the given formatter.

impl Default for SOFOConfig

fn default() -> Self

Returns the “default value” for a type.