Struct PruneTrainer 

pub struct PruneTrainer { /* private fields */ }

Prune-finetune trainer that orchestrates the full pipeline.

Example

use entrenar::prune::{PruneTrainer, PruneTrainerConfig, PruningConfig};

fn example() -> Result<(), Box<dyn std::error::Error>> {
    let config = PruneTrainerConfig::new()
        .with_pruning(PruningConfig::default().with_target_sparsity(0.5))
        .with_finetune_epochs(3);

    let mut trainer = PruneTrainer::new(config);
    trainer.run()?;
    Ok(())
}

Implementations

impl PruneTrainer

pub fn new(config: PruneTrainerConfig) -> Self

Create a new prune trainer.

pub fn config(&self) -> &PruneTrainerConfig

Get the configuration.

pub fn pipeline(&self) -> &PruneFinetunePipeline

Get the current pipeline state.

pub fn pipeline_mut(&mut self) -> &mut PruneFinetunePipeline

Get mutable access to the pipeline.

pub fn stage(&self) -> PruningStage

Get the current stage.

pub fn metrics(&self) -> &PruningMetrics

Get the metrics.

pub fn current_epoch(&self) -> usize

Get the current fine-tuning epoch.

pub fn is_complete(&self) -> bool

Check if the trainer is complete.

pub fn succeeded(&self) -> bool

Check if training succeeded.

pub fn error(&self) -> Option<&str>

Get the error message if failed.

pub fn initialize(&mut self) -> Result<(), String>

Initialize the trainer and load calibration data.

pub fn calibrate(&mut self) -> Result<(), String>

Run calibration phase.

In a real implementation, this would:

1. Run forward passes through the model
2. Collect activation statistics for each layer
3. Store statistics in the calibration collector

pub fn prune(&mut self) -> Result<(), String>

Run the pruning phase.

In a real implementation, this would:

1. Compute importance scores using calibration data
2. Generate sparsity masks
3. Apply masks to model weights

pub fn finetune(&mut self) -> Result<(), String>

Run the fine-tuning phase.

In a real implementation, this would:

1. Set up optimizer with fine-tuning learning rate
2. Run training epochs
3. Track loss and metrics

pub fn evaluate(&mut self) -> Result<(), String>

Run evaluation phase.

pub fn export(&mut self) -> Result<(), String>

Run export phase.

pub fn run(&mut self) -> Result<PruningMetrics, String>

Run the full prune-finetune pipeline.

pub fn reset(&mut self)

Reset the trainer to initial state.

Trait Implementations

impl Clone for PruneTrainer

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for PruneTrainer

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

Formats the value using the given formatter.