Struct AdaGrad 

pub struct AdaGrad { /* private fields */ }

AdaGrad optimizer

Implementations

impl AdaGrad

pub fn new(learning_rate: f32, epsilon: f32) -> Self

Create new AdaGrad optimizer 新しいAdaGradオプティマイザーを作成

pub fn default_params(learning_rate: f32) -> Self

Create AdaGrad with default parameters デフォルトパラメータでAdaGradを作成

pub fn with_weight_decay( learning_rate: f32, epsilon: f32, weight_decay: f32, ) -> Self

Create AdaGrad with weight decay 重み減衰付きAdaGradを作成

pub fn with_initial_accumulator( learning_rate: f32, epsilon: f32, initial_accumulator_value: f32, ) -> Self

Create AdaGrad with initial accumulator value 初期アキュムレータ値付きAdaGradを作成

Trait Implementations

impl Clone for AdaGrad

fn clone(&self) -> AdaGrad

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for AdaGrad

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

Formats the value using the given formatter.

impl Optimizer for AdaGrad

fn step(&mut self, param: &Tensor<f32>, grad: &Tensor<f32>)

Update parameters with gradients

fn learning_rate(&self) -> f32

Get learning rate

fn set_learning_rate(&mut self, lr: f32)

Set learning rate

fn state_dict(&self) -> HashMap<String, f32>

Get optimizer state

fn load_state_dict(&mut self, state: HashMap<String, f32>)

Load optimizer state

fn zero_grad(&mut self)

Zero gradients (if needed)