Terminal Dashboard - Entrenar - Training & Optimization Library
Description: A comprehensive guide to building neural network training systems with autograd, optimizers, LoRA/QLoRA, and quantization using EXTREME TDD methodology

# Terminal Dashboard

ASCII terminal dashboard for real-time training visualization.

## Usage

    #![allow(unused)]
    fn main() {
    use entrenar::monitor::{Dashboard, MetricsCollector, Metric};

    let mut collector = MetricsCollector::new();
    let mut dashboard = Dashboard::new();

    // During training
    for epoch in 0..100 {
        collector.record(Metric::Loss, loss);
        collector.record(Metric::Accuracy, accuracy);

        // Update and render
        dashboard.update(collector.summary());
        println!("{}", dashboard.render_ascii());
    }
    }

## Output Example

    ═══════════════════════════════════════════════════════════════
                        TRAINING DASHBOARD
    ═══════════════════════════════════════════════════════════════

    Loss:     0.1234  [▁▂▃▄▅▆▇█▇▆▅▄▃▂▁]  ↓ Improving
    Accuracy: 0.9567  [▁▁▂▃▄▅▆▇▇▇▇▇▇▇█]  ↑ Improving

    Statistics:
      Loss     - mean: 0.3421, std: 0.1234, min: 0.1234, max: 0.8901
      Accuracy - mean: 0.8234, std: 0.0567, min: 0.5000, max: 0.9567

    ═══════════════════════════════════════════════════════════════

## Sparklines

The dashboard uses Unicode sparkline characters to show metric history:

    #![allow(unused)]
    fn main() {
    let sparkline = dashboard.sparkline(&Metric::Loss);
    // Returns: "▁▂▃▄▅▆▇█▇▆▅▄▃▂▁"
    }

Characters map values to 8 levels: `▁▂▃▄▅▆▇█`

## Configuration

    #![allow(unused)]
    fn main() {
    use entrenar::monitor::DashboardConfig;

    let config = DashboardConfig {
        width: 80,
        height: 24,
        refresh_ms: 1000,
    };

    let dashboard = Dashboard::with_config(config);
    }