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Terminal based machine learning training monitor

Project description

Aliyah - ML Training Monitor

Aliyah is a terminal-based machine learning training monitor that lets you visualize and interact with your model training in real-time.

Installation

# Install both components
pip install aliyah
cargo install aliyah

# Or from source
git clone https://github.com/lovechants/Aliyah.git
cd Aliyah
cargo build --release
pip install -e python/

Features

  • Real-time visualization of model training
  • Interactive controls (pause/resume/stop)
  • Network architecture visualization
  • Training metrics plotting
  • System resource monitoring
  • Support for PyTorch, JAX, and other frameworks

Usage

from aliyah import monitor, trainingmonitor

# Inside your training code
with trainingmonitor() as monitor:
    for epoch in range(epochs):
        for batch_idx, (data, target) in enumerate(train_loader):
            # Your training code
            loss = ...
            accuracy = ...
            
            # Log metrics
            monitor.log_batch(batch_idx, loss, accuracy, extra_metrics=extra_metrics)
            
            # Check if user paused/stopped
            if not monitor.check_control():
                break
        
        # Log epoch metrics
        monitor.log_epoch(epoch, val_loss, val_accuracy)

Keyboard Controls

  • q/ESC: Quit
  • p/SPACE: Pause/Resume training
  • s: Stop training
  • e: Toggle error log
  • ↑/↓: Scroll logs
  • c: Clear error log
  • h: Show help
  • tab/n: Show node information
  • click: Switch training and node panel
  • o: Output panel

Framework Support

  • ✅ PyTorch
  • 🚧 JAX
  • 🚧 TensorFlow/Keras
  • 🚧 Scikit-Learn

License

MIT

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