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Running
on
Zero
Running
on
Zero
File size: 2,093 Bytes
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import os
import torch
import subprocess
def setup_for_distributed(is_master):
"""
This function disables printing when not in master process
"""
import builtins as __builtin__
builtin_print = __builtin__.print
def print(*args, **kwargs):
force = kwargs.pop('force', False)
if is_master or force:
builtin_print(*args, **kwargs)
__builtin__.print = print
def init_distributed_mode(args):
if 'RANK' in os.environ and 'WORLD_SIZE' in os.environ:
args.rank = int(os.environ["RANK"])
args.world_size = int(os.environ['WORLD_SIZE'])
args.gpu = int(os.environ['LOCAL_RANK'])
args.dist_url = 'env://'
os.environ['LOCAL_SIZE'] = str(torch.cuda.device_count())
elif 'SLURM_PROCID' in os.environ:
proc_id = int(os.environ['SLURM_PROCID'])
ntasks = int(os.environ['SLURM_NTASKS'])
node_list = os.environ['SLURM_NODELIST']
num_gpus = torch.cuda.device_count()
addr = subprocess.getoutput(
'scontrol show hostname {} | head -n1'.format(node_list))
os.environ['MASTER_PORT'] = os.environ.get('MASTER_PORT', '29500')
os.environ['MASTER_ADDR'] = addr
os.environ['WORLD_SIZE'] = str(ntasks)
os.environ['RANK'] = str(proc_id)
os.environ['LOCAL_RANK'] = str(proc_id % num_gpus)
os.environ['LOCAL_SIZE'] = str(num_gpus)
args.dist_url = 'env://'
args.world_size = ntasks
args.rank = proc_id
args.gpu = proc_id % num_gpus
else:
print('Not using distributed mode')
args.distributed = False
return
args.distributed = True
torch.cuda.set_device(args.gpu)
args.dist_backend = 'nccl'
print('| distributed init (rank {}): {}'.format(
args.rank, args.dist_url), flush=True)
torch.distributed.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
world_size=args.world_size, rank=args.rank)
torch.distributed.barrier()
setup_for_distributed(args.rank == 0)
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