Distributed Training, Model Parallelism, Data Parallelism, Pytorch, Aurorain.
that the first task should happen once per training, but the last two tasks should occur in each iteration. PyTorch Distributed Data Parallel (DDP) implements data parallelism at the module level for running across multiple machines. It can work together with the PyTorch model parallel. DDP