LightningModule abstraction
Enables complex interactions of PyTorch nn.Module objects within training, validation, and testing steps.
Multi-GPU/TPU/HPU training
Supports distributed training on multiple GPUs, TPUs, and HPUs without code modifications.
Built-in testing
Provides integrated testing capabilities to avoid the need for custom test implementations.
Trainer class
Automates training loop details and supports plugins for various backends, precision libraries, and clusters.
Precision control
Supports 64-bit, 32-bit, and 16-bit floating point operations with regular and mixed precision settings.
Checkpoint management
Enables saving and loading of model checkpoints for reproducibility and reuse.