Struct RMSprop 

pub struct RMSprop { /* private fields */ }

RMSprop optimizer.

Maintains a moving average of squared gradients for adaptive learning rates.

Update rule:

v_t = α * v_{t-1} + (1 - α) * grad²
param = param - lr * grad / (√v_t + ε)

Implementations

impl RMSprop

pub fn new(params: Vec<&mut Tensor>, lr: f32) -> Self

Create a new RMSprop optimizer.

Default: α=0.99, ε=1e-8

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

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

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

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

pub fn step_with_params(&mut self, params: &mut [&mut Tensor])

Trait Implementations

impl Debug for RMSprop

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

Formats the value using the given formatter.

impl Optimizer for RMSprop

fn step(&mut self)

Perform a single optimization step using computed gradients.

fn zero_grad(&mut self)

Zero all parameter gradients.

fn lr(&self) -> f32

Get current learning rate.

fn set_lr(&mut self, lr: f32)

Set learning rate (for schedulers).