PyTorch Lightning: Organized Deep Learning

PyTorch Lightning separates research code from engineering boilerplate. Automatic distributed training. Built-in logging and checkpointing. Hardware-agnostic code.

Module Structure

LightningModule organizes model code. Define training_step for forward pass and loss. Configure optimizers in configure_optimizers. Trainer handles training loop.

• Define models as LightningModule subclasses
• Implement training_step for training logic
• Use Trainer for training configuration
• Leverage callbacks for custom behavior
• Log metrics automatically

Scaling

Automatic multi-GPU and multi-node training. Mixed precision with single flag. Gradient accumulation for large batches. Profile performance easily.