Struct ParallelAdam 

pub struct ParallelAdam { /* private fields */ }

Parallel Adam optimizer with multi-threaded parameter updates.

Implementations

impl ParallelAdam

pub fn new(lr: f32, betas: (f32, f32), eps: f32, weight_decay: f32) -> Self

Creates a new parallel Adam optimizer.

pub fn with_config( lr: f32, betas: (f32, f32), eps: f32, weight_decay: f32, config: ParallelConfig, ) -> Self

Creates a parallel Adam optimizer with custom configuration.

pub fn update_parallel( &self, updates: Vec<(String, &mut [f32], &[f32])>, ) -> Result<()>

Updates multiple parameters in parallel.

pub fn parallel_stats(&self) -> ParallelStats

Gets parallel performance statistics.

pub fn configure_thread_pool(&self) -> Result<()>

Configures thread pool for optimal performance.

Trait Implementations

impl BatchUpdate for ParallelAdam

fn update_batch(&mut self, batch: Vec<(&mut Tensor, &Tensor)>) -> Result<()>

Updates multiple parameters in a single batch operation.

impl Debug for ParallelAdam

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

Formats the value using the given formatter.

impl Optimizer for ParallelAdam

fn update(&mut self, parameter: &mut Tensor, grad: &Tensor) -> Result<()>

Updates a parameter based on its gradient.

fn zero_grad(&mut self)

Clears all accumulated gradients.

fn step(&mut self)

Performs a single optimization step.

fn get_lr(&self) -> f32

Gets the current learning rate.

fn set_lr(&mut self, lr: f32)

Sets a new learning rate.

fn accumulate_grad( &mut self, parameter: &mut Tensor, grad: &Tensor, ) -> Result<(), TrustformersError>

Accumulates gradients for gradient accumulation.

fn apply_accumulated_grads( &mut self, accumulation_steps: usize, ) -> Result<(), TrustformersError>

Applies accumulated gradients after gradient accumulation.