Struct MobileOptimizer 

pub struct MobileOptimizer { /* private fields */ }

Mobile-optimized optimizer with memory and latency constraints

Implementations

impl MobileOptimizer

pub fn new( base_optimizer: Box<dyn Optimizer>, config: HardwareAwareConfig, ) -> Result<Self>

pub fn compress_gradients(&self, gradients: &[Tensor]) -> Result<Vec<Tensor>>

Compresses gradients to the configured precision for mobile deployment.

The returned tensors carry the reduced dtype (F16 for CompressionRatio::Half), so the memory saving is real and observable via Tensor::size_bytes.

Errors

Returns an error when a gradient’s dtype cannot be converted.

Trait Implementations

impl Optimizer for MobileOptimizer

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.