Function save_training 

pub fn save_training<B: Backend>(
    path: impl AsRef<Path>,
    checkpoint: &TrainingCheckpoint<B>,
) -> Result<()>

Save a complete training checkpoint to a file.

This saves model parameters, optimizer state, epoch, and loss history, enabling full training resume.

use shrew::checkpoint::{self, TrainingCheckpoint};
use shrew::prelude::*;

// During training:
let ckpt = TrainingCheckpoint::<CpuBackend>::new()
    .with_epoch(10)
    .with_global_step(5000)
    .with_best_loss(0.032)
    .with_loss_history(vec![0.5, 0.2, 0.1, 0.05, 0.032]);
checkpoint::save_training("training.shrew", &ckpt).unwrap();