README.md

comm-ddp

An easy-to-use communication tools for pytorch-DDP (single-node with multi-GPUs).

• features: launch_DDP, cleanup, rank number, world size, gather, etc.

• Installation

pip install comm-ddp

• Import

from comm_ddp import comm

• Launch

comm.launch_DDP()

• print iff. main_rank

comm.mprint("Hello World") # only main_rank would print

• rank & world size

local_rank = comm.get_local_rank()
word_size = comm.get_world_size()

• gather

comm.gather()
comm.all_gather()

• Demo Usecases: demo.py (see some examples).

Don't forget these:

wrap model with DDP

from torch.nn.parallel import DistributedDataParallel as DDP

def to_dev(x, device='cuda'):
  rank=comm.get_local_rank()
  dst = torch.device(device) is rank is None else rank
  
  x = x.to(dst)
  
  if isinstance(x, nn.Module):
    x = DDP(x, device_ids=[rank % torch.cuda.device_count()], find_unused_parameters=False)
  
  return x
  
model = to_dev(model)  

and launch code via

torchrun --nproc_per_node=4 train.py