Helper method to adapt optimizer for non-distributed and distributed configurations (supporting all available backends from
Internally, this method is no-op for non-distributed and torch native distributed configuration.
For XLA distributed configuration, we create a new class that inherits from provided optimizer. The goal is to override the step() method with specific xm.optimizer_step implementation.
For Horovod distributed configuration, optimizer is wrapped with Horovod Distributed Optimizer and its state is broadcasted from rank 0 to all other processes.
optimizer (torch.optim.optimizer.Optimizer) – input torch optimizer
kwargs (Any) – kwargs to Horovod backend’s DistributedOptimizer.
- Return type
import ignite.distributed as idist optimizer = idist.auto_optim(optimizer)
Changed in version 0.4.2: Added Horovod distributed optimizer.
Changed in version 0.4.7: Added kwargs to