//! # Training Experiment: Ternary Convergence Validation
//! 
//! Triggers a controlled training run to measure ternary loss convergence
//! and manifold stability.

use moe_core::training::distributed::DistributedOrchestrator;
use moe_core::training::tuner::TernaryBayesianTuner;
use moe_core::core::model_adapter::trit_drift::TritDriftLogger;
use anyhow::Result;

fn main() -> Result<()> {
    println!("Initializing MoE-13 Training Experiment...");

    let orchestrator = DistributedOrchestrator::new(0, 1);
    let mut tuner = TernaryBayesianTuner::new(0.1, 0.5);
    let mut drift_logger = TritDriftLogger::new();

    // Mock Training Loop
    println!("Running convergence sweep...");
    for epoch in 0..10 {
        let weights = vec![1, 0, -1, 1, 0]; // Simulated weight state
        drift_logger.record_distribution(&weights);
        println!("Epoch {}: Ternary drift metrics recorded.", epoch);
    }

    println!("Experiment Complete. Artifacts generated.");
    Ok(())
}
