🚀 Feature

Pytorch lightning recently added native support for MS DeepSpeed.

I believe it is also helpful for users if ignite incorporates the DeepSpeed pipeline for memory-efficient distributed training.

1. for idist.auto_model ..?

To initialize the DeepSpeed engine:

model_engine, optimizer, _, _ = deepspeed.initialize(args=cmd_args,
                                                     model=model,
                                                     model_parameters=params)

And for distributed environment setup, we need to replace torch.distributed.init_process_group(...) to deepspeed.init_distributed()

2. checkpoint handler

slightly different thing for checkpointing

model_engine.save_checkpoint(args.save_dir, ckpt_id, client_sd = client_sd)