pub struct DistillationTrainer<T: TeacherModel> {
pub config: TrainerConfig,
/* private fields */
}Expand description
Knowledge Distillation Trainer
Orchestrates the training loop for distilling knowledge from a teacher model to a student model.
Fields§
§config: TrainerConfigConfiguration
Implementations§
Source§impl<T: TeacherModel> DistillationTrainer<T>
impl<T: TeacherModel> DistillationTrainer<T>
Sourcepub fn new(config: TrainerConfig, teacher: T) -> Self
pub fn new(config: TrainerConfig, teacher: T) -> Self
Create new trainer with teacher model
Sourcepub fn state(&self) -> &TrainingState
pub fn state(&self) -> &TrainingState
Get current training state
Sourcepub fn compute_loss(
&self,
student_logits: &Array2<f32>,
teacher_logits: &Array2<f32>,
targets: &[usize],
student_hidden: Option<&[Array2<f32>]>,
teacher_hidden: Option<&[Array2<f32>]>,
student_attention: Option<&[Array2<f32>]>,
teacher_attention: Option<&[Array2<f32>]>,
) -> f32
pub fn compute_loss( &self, student_logits: &Array2<f32>, teacher_logits: &Array2<f32>, targets: &[usize], student_hidden: Option<&[Array2<f32>]>, teacher_hidden: Option<&[Array2<f32>]>, student_attention: Option<&[Array2<f32>]>, teacher_attention: Option<&[Array2<f32>]>, ) -> f32
Compute total loss for a batch
Combines distillation loss with optional progressive and attention transfer.
Sourcepub fn is_parameter_efficient(&self) -> bool
pub fn is_parameter_efficient(&self) -> bool
Check if using LoRA/QLoRA for student fine-tuning
Sourcepub fn estimate_total_memory(&self) -> u64
pub fn estimate_total_memory(&self) -> u64
Estimate total memory requirements
Sourcepub fn simulate_step(&mut self, loss: f32)
pub fn simulate_step(&mut self, loss: f32)
Simulate one training step (for testing)
Sourcepub fn simulate_epoch(&mut self)
pub fn simulate_epoch(&mut self)
Simulate epoch boundary
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impl<T> UnwindSafe for DistillationTrainer<T>where
T: UnwindSafe,
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