# -*- coding: utf-8 -*- # MegEngine is Licensed under the Apache License, Version 2.0 (the "License") # # Copyright (c) 2014-2021 Megvii Inc. All rights reserved. # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. import functools import multiprocessing as mp import os import queue from .. import _exit from ..core._imperative_rt.core2 import full_sync from ..device import get_device_count from ..logger import get_logger from .group import _set_machine_ranks, group_barrier, init_process_group from .helper import _check_device_initialized from .server import Client, Server WARN_SUBPROCESS_EXIT_WITHOUT_RETURN = ( "subprocess exited with code 0 but did not return a value" ) def _run_wrapped( func, is_multimachine, master_ip, port, world_size, rank, dev, device_type, args, kwargs, backend, queue: mp.Queue, machine_ranks: list, ): r"""Init distributed process group and run wrapped function.""" _check_device_initialized(device_type, dev) init_process_group( master_ip=master_ip, port=port, world_size=world_size, rank=rank, device=dev, backend=backend, device_type=device_type, ) # set NCCL_LAUNCH_MODE to avoid deadlock os.environ["NCCL_LAUNCH_MODE"] = "PARALLEL" _set_machine_ranks(machine_ranks) if is_multimachine: group_barrier() ret = func(*args, **kwargs) queue.put((dev, ret)) full_sync() if is_multimachine: group_barrier() _exit(0) class launcher: r"""Decorator for launching multiple processes in single-machine multi-gpu training. Args: func: the function you want to launch in distributed mode. n_gpus: how many devices each node. world_size: how many devices totally. rank_start: start number for rank. master_ip: ip address for master node (where the rank 0 is). port: server port for distributed server. backend: set default collective communication backend. """ def __new__(cls, *args, **kwargs): if not args: return functools.partial(cls, **kwargs) return super().__new__(cls) def __init__( self, func, n_gpus=None, world_size=None, rank_start=0, master_ip="localhost", port=0, device_type="xpu", backend="nccl", ): self.func = func self.n_gpus = n_gpus if n_gpus is not None else get_device_count(device_type) self.world_size = world_size if world_size is not None else self.n_gpus self.rank_start = rank_start self.master_ip = master_ip self.port = port self.device_type = device_type self.backend = backend # master node create server if self.rank_start == 0: self.server = Server(self.port) self.port = self.server.py_server_port else: assert self.port != 0, "you have to assign a port for distributed server" def __call__(self, *args, **kwargs): procs = [] queue = mp.Queue(self.n_gpus) results = [None] * self.n_gpus machine_ranks = [i + self.rank_start for i in range(self.n_gpus)] for dev in range(self.n_gpus): p = mp.Process( target=_run_wrapped, args=( self.func, self.world_size > self.n_gpus, self.master_ip, self.port, self.world_size, dev + self.rank_start, dev, self.device_type, args, kwargs, self.backend, queue, machine_ranks, ), ) p.start() procs.append(p) devs = list(range(self.n_gpus)) def terminate(): for dev in devs: procs[dev].terminate() devs.clear() result_count = 0 while len(devs) > 0: left = [] # check all processes in one second time_to_wait = 1.0 / len(devs) for dev in devs: procs[dev].join(time_to_wait) code = procs[dev].exitcode # terminate processes if one of them has failed if code != 0 and code != None: terminate() assert ( code == 0 or code == None ), "subprocess {} exit with code {}".format(dev + self.rank_start, code) if code == None: left.append(dev) # DO NOT delete it, multiprocess.Queue has small buffer # fetch data early to avoid dead lock if not queue.empty(): result_count += 1 dev, ret = queue.get_nowait() results[dev] = ret devs = left while not queue.empty(): result_count += 1 dev, ret = queue.get_nowait() results[dev] = ret if result_count < self.n_gpus: get_logger().warning(WARN_SUBPROCESS_EXIT_WITHOUT_RETURN) return results