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""" | |
Helpers for distributed training. | |
""" | |
import io | |
import os | |
import socket | |
import blobfile as bf | |
from mpi4py import MPI | |
import torch as th | |
import torch.distributed as dist | |
# Change this to reflect your cluster layout. | |
# The GPU for a given rank is (rank % GPUS_PER_NODE). | |
GPUS_PER_NODE = th.cuda.device_count() | |
SETUP_RETRY_COUNT = 3 | |
def setup_dist(): | |
""" | |
Setup a distributed process group. | |
""" | |
if dist.is_initialized(): | |
return | |
comm = MPI.COMM_WORLD | |
backend = "gloo" if not th.cuda.is_available() else "nccl" | |
if backend == "gloo": | |
hostname = "localhost" | |
else: | |
hostname = socket.gethostbyname(socket.getfqdn()) | |
if not os.environ.get("MASTER_ADDR"): | |
os.environ["MASTER_ADDR"] = comm.bcast(hostname, root=0) | |
os.environ["RANK"] = str(comm.rank) | |
os.environ["WORLD_SIZE"] = str(comm.size) | |
port = comm.bcast(_find_free_port(), root=0) | |
if not os.environ.get("MASTER_PORT"): | |
os.environ["MASTER_PORT"] = str(port) | |
th.cuda.set_device(dev()) | |
dist.init_process_group(backend=backend, init_method="env://") | |
def dev(): | |
""" | |
Get the device to use for torch.distributed. | |
""" | |
if th.cuda.is_available(): | |
return th.device(f"cuda:{MPI.COMM_WORLD.Get_rank() % GPUS_PER_NODE}") | |
return th.device("cpu") | |
def load_state_dict(path, **kwargs): | |
""" | |
Load a PyTorch file without redundant fetches across MPI ranks. | |
""" | |
if MPI.COMM_WORLD.Get_rank() == 0: | |
with bf.BlobFile(path, "rb") as f: | |
data = f.read() | |
else: | |
data = None | |
data = MPI.COMM_WORLD.bcast(data) | |
return th.load(io.BytesIO(data), **kwargs) | |
def sync_params(params): | |
""" | |
Synchronize a sequence of Tensors across ranks from rank 0. | |
""" | |
for p in params: | |
with th.no_grad(): | |
dist.broadcast(p, 0) | |
def _find_free_port(): | |
try: | |
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | |
s.bind(("", 0)) | |
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) | |
return s.getsockname()[1] | |
finally: | |
s.close() | |