Struct MixedPrecisionTrainer 

pub struct MixedPrecisionTrainer { /* private fields */ }

Mixed precision trainer for embeddings

Implementations

impl MixedPrecisionTrainer

pub fn new(config: MixedPrecisionConfig) -> Self

Create new mixed precision trainer

pub fn to_fp16(&self, tensor: &Array1<f32>) -> Array1<f32>

Convert float32 tensor to float16 (simulated with f32)

Note: Rust doesn’t have native float16, so we simulate by clamping range

pub fn to_fp32(&self, tensor: &Array1<f32>) -> Array1<f32>

Convert float16 back to float32 (no-op in simulation)

pub fn scale_loss(&self, loss: f32) -> f32

Scale loss for backward pass

pub fn unscale_gradients(&self, gradients: &Array1<f32>) -> Result<Array1<f32>>

Unscale gradients after backward pass

pub fn update_parameters( &mut self, parameters: &mut Array1<f32>, gradients: &Array1<f32>, learning_rate: f32, ) -> Result<()>

Update parameters with mixed precision

pub fn get_stats(&self) -> &MixedPrecisionStats

Get current statistics

pub fn reset_stats(&mut self)

Reset statistics

pub fn estimate_memory_savings(&mut self, num_parameters: usize)

Estimate memory savings

pub fn update_gradient_stats(&mut self, gradients: &Array1<f32>)

Update average gradient norm

pub fn is_stable(&self) -> bool

Check if training is stable

pub fn config(&self) -> &MixedPrecisionConfig

Get configuration