Struct ExponentialLr 

pub struct ExponentialLr { /* private fields */ }

Exponential learning-rate scheduler.

Every step, the optimizer learning rate is multiplied by gamma: lr = lr * gamma.

Implementations

impl ExponentialLr

pub fn new(gamma: f32) -> Result<Self, OptimError>

Creates exponential scheduler with gamma in (0, 1].

pub fn gamma(&self) -> f32

Returns configured decay factor.

pub fn epoch(&self) -> usize

Returns number of already-processed step calls.

pub fn reset(&mut self)

Resets internal epoch counter.

pub fn step<O: LearningRate>( &mut self, optimizer: &mut O, ) -> Result<f32, OptimError>

Advances scheduler by one epoch and returns resulting optimizer LR.

Trait Implementations

impl Clone for ExponentialLr

fn clone(&self) -> ExponentialLr

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ExponentialLr

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

Formats the value using the given formatter.

impl LrScheduler for ExponentialLr

fn step<O: LearningRate>( &mut self, optimizer: &mut O, ) -> Result<f32, OptimError>

Advances scheduler by one epoch and returns resulting optimizer LR.

fn epoch(&self) -> usize

Returns number of already-processed step calls.

fn reset(&mut self)

Resets scheduler internal state.

impl PartialEq for ExponentialLr

fn eq(&self, other: &ExponentialLr) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for ExponentialLr