Introduction to Lightning Fabric

Lightning Fabric is an open-source component of Lightning 2.0 designed to provide PyTorch users with scalable training capabilities while preserving direct control over their training loops. Positioned between raw PyTorch and the higher-level PyTorch Lightning Trainer, it lets developers adapt existing code for CPUs, GPUs, TPUs, mixed precision, and distributed environments through a small number of setup calls and runtime configuration options rather than repeated code changes. Fabric includes optional tools for distributed strategies such as DDP, DeepSpeed, and FSDP, as well as logging, callbacks, gradient accumulation, distributed collectives, and checkpointing that supports sharded models. It can also serve as a foundation for custom trainers, including those organized around LightningModule hooks, while allowing users to select only the features they need. Lightning 2.0 presents Fabric as its flexible option for researchers and framework builders, alongside PyTorch Lightning’s established feature-rich Trainer for users seeking faster, more standardized experimentation.

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