Distributed Training, Model Parallelism, Data Parallelism, Pytorch, Aurorain.
the corresponding gradient is computed in the backward pass. DDP then uses that signal to trigger gradient synchronization across processes. So there are three main steps to set up and run DDP in PyTorch: Set up distributed system via torch.distributed. Define the DDP modeling by torch.nn.parallel.