| | |
|---|
| | | |
|---|
| | | local_rank = int(os.environ.get('LOCAL_RANK', 0)) |
|---|
| | | # Check if we are using DDP or FSDP |
|---|
| | | use_ddp = 'WORLD_SIZE' in os.environ |
|---|
| | | use_ddp = 'WORLD_SIZE' in os.environ and os.environ["WORLD_SIZE"] > 1 |
|---|
| | | use_fsdp = kwargs.get("use_fsdp", None) |
|---|
| | | if use_ddp or use_fsdp: |
|---|
| | | dist.init_process_group(backend=kwargs.get("backend", "nccl"), init_method='env://') |
|---|
| | |
|---|
| | | |
|---|
| | | if use_ddp: |
|---|
| | | model = model.cuda(local_rank) |
|---|
| | | model = DDP(model, device_ids=[local_rank]) |
|---|
| | | model = DDP(model, device_ids=[local_rank], |
|---|
| | | find_unused_parameters=kwargs.get("train_conf", {}).get("find_unused_parameters", False)) |
|---|
| | | elif use_fsdp: |
|---|
| | | model = FSDP(model).cuda(local_rank) |
|---|
| | | else: |
|---|
| | |
|---|
| | | torch.distributed.destroy_process_group() |
|---|
| | | |
|---|
| | | |
|---|
| | | |
|---|
| | | def train(epoch, model, op): |
|---|
| | | pass |
|---|
| | | |
|---|
| | | def val(): |
|---|
| | | pass |
|---|
| | | |
|---|
| | | |
|---|
| | | if __name__ == "__main__": |
|---|
| | | main() |
|---|
