| import torch
|
| import torch.nn as nn
|
| import subprocess
|
| import sys
|
| import os
|
| from lib.utils.tools.logger import Logger as Log
|
|
|
|
|
| def is_distributed():
|
| return torch.distributed.is_initialized()
|
|
|
| def get_world_size():
|
| if not torch.distributed.is_initialized():
|
| return 1
|
| return torch.distributed.get_world_size()
|
|
|
| def get_rank():
|
| if not torch.distributed.is_initialized():
|
| return 0
|
| return torch.distributed.get_rank()
|
|
|
| def all_reduce_numpy(array):
|
| tensor = torch.from_numpy(array).cuda()
|
| torch.distributed.all_reduce(tensor)
|
| return tensor.cpu().numpy()
|
|
|
| def handle_distributed(args, main_file):
|
| if not args.distributed:
|
| os.environ['CUDA_VISIBLE_DEVICES'] = ','.join(map(str, args.gpu))
|
| return
|
|
|
| if args.local_rank >= 0:
|
| _setup_process_group(args)
|
| return
|
|
|
| current_env = os.environ.copy()
|
| if current_env.get('CUDA_VISIBLE_DEVICES') is None:
|
| current_env['CUDA_VISIBLE_DEVICES'] = ','.join(map(str, args.gpu))
|
| world_size = len(args.gpu)
|
| else:
|
| world_size = len(current_env['CUDA_VISIBLE_DEVICES'].split(','))
|
|
|
| current_env['WORLD_SIZE'] = str(world_size)
|
|
|
| print('World size:', world_size)
|
|
|
| python_exec = sys.executable
|
| command_args = sys.argv
|
| Log.info('{}'.format(command_args))
|
| try:
|
| main_index = command_args.index('main_contrastive.py')
|
| except:
|
| main_index = command_args.index('main.py')
|
|
|
| command_args = command_args[main_index+1:]
|
| print(command_args)
|
| command_args = [
|
| python_exec, '-u',
|
| '-m', 'torch.distributed.launch',
|
| '--nproc_per_node', str(world_size),
|
| '--master_port', str(29961),
|
| main_file,
|
| ] + command_args
|
| process = subprocess.Popen(command_args, env=current_env)
|
| process.wait()
|
| if process.returncode != 0:
|
| raise subprocess.CalledProcessError(returncode=process.returncode,
|
| cmd=command_args)
|
| sys.exit(process.returncode)
|
|
|
| def _setup_process_group(args):
|
| local_rank = args.local_rank
|
|
|
| torch.cuda.set_device(local_rank)
|
| torch.distributed.init_process_group(
|
| 'nccl',
|
| init_method='env://',
|
|
|
| ) |
