lightning.fabric.strategies

Strategies

Strategy	Base class for all strategies that change the behaviour of the training, validation and test- loop.
DDPStrategy	Strategy for multi-process single-device training on one or multiple nodes.
DataParallelStrategy	Implements data-parallel training in a single process, i.e., the model gets replicated to each device and each gets a split of the data.
FSDPStrategy	Strategy for Fully Sharded Data Parallel provided by torch.distributed.
DeepSpeedStrategy	Provides capabilities to run training using the DeepSpeed library, with training optimizations for large billion parameter models.
XLAStrategy	Strategy for training multiple TPU devices using the torch_xla.distributed.xla_multiprocessing.spawn() method.
XLAFSDPStrategy	Strategy for training multiple XLA devices using the torch_xla.distributed.xla_fully_sharded_data_parallel.XlaFullyShardedDataParallel() method.
ParallelStrategy	Strategy for training with multiple processes in parallel.
SingleDeviceStrategy	Strategy that handles communication on a single device.
SingleDeviceXLAStrategy	Strategy for training on a single XLA device.
ModelParallelStrategy	Enables user-defined parallelism applied to a model.