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Paddle/python/paddle/distributed/utils.py

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# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import functools
import logging
import socket
import time
import os
import signal
import copy
import sys
import subprocess
from contextlib import closing
import socket
logger = logging.getLogger("root")
logger.propagate = False
class Hdfs(object):
def __init__(self):
self.hdfs_ugi = None
self.hdfs_name = None
self.hdfs_path = None
def is_valid(self):
return self.hdfs_ugi is not None and \
self.hdfs_name is not None and \
self.hdfs_path is not None
def __str__(self):
return "hdfs_ugi:{} hdfs_name:{} hdfs_path{}".format(
self.hdfs_ugi, self.hdfs_name, self.hdfs_path)
def __eq__(self, n):
return self.hdfs_ugi == n.hdfs_ugi and \
self.hdfs_name == n.hdfs_name and \
self.hdfs_path == n.hdfs_path
def __ne__(self, n):
return not self == n
class Cluster(object):
def __init__(self, hdfs):
self.job_server = None
self.pods = []
self.hdfs = None
self.job_stage_flag = None
def __str__(self):
return "job_server:{} pods:{} job_stage_flag:{} hdfs:{}".format(
self.job_server, [str(pod) for pod in self.pods],
self.job_stage_flag, self.hdfs)
def __eq__(self, cluster):
if len(self.pods) != len(cluster.pods):
return False
for a, b in zip(self.pods, cluster.pods):
if a != b:
return False
if self.job_stage_flag != cluster.job_stage_flag:
return False
return True
def __ne__(self, cluster):
return not self.__eq__(cluster)
def update_pods(cluster):
self.pods = copy.copy(cluster.pods)
def trainers_nranks(self):
return len(self.trainers_endpoints())
def pods_nranks(self):
return len(self.pods)
def trainers_endpoints(self):
r = []
for pod in self.pods:
for t in pod.trainers:
r.append(t.endpoint)
return r
def pods_endpoints(self):
r = []
for pod in self.pods:
ep = "{}:{}".format(pod.addr, pod.port)
assert pod.port != None and pod.addr != None, "{} not a valid endpoint".format(
ep)
r.append(ep)
return r
def get_pod_by_id(self, pod_id):
for pod in self.pods:
if str(pod_id) == str(pod.id):
return pod
return None
class JobServer(object):
def __init__(self):
self.endpoint = None
def __str__(self):
return "{}".format(self.endpoint)
def __eq__(self, j):
return self.endpint == j.endpoint
def __ne__(self, j):
return not self == j
class Trainer(object):
def __init__(self):
self.gpus = []
self.endpoint = None
self.rank = None
def __str__(self):
return "gpu:{} endpoint:{} rank:{}".format(self.gpus, self.endpoint,
self.rank)
def __eq__(self, t):
if len(self.gpus) != len(t.gpus):
return False
if self.endpoint != t.endpoint or \
self.rank != t.rank:
return False
for a, b in zip(self.gpus, t.gpus):
if a != b:
return False
return True
def __ne__(self, t):
return not self == t
def rank(self):
return self.rank
class Pod(object):
def __init__(self):
self.rank = None
self.id = None
self.addr = None
self.port = None
self.trainers = []
self.gpus = []
def __str__(self):
return "rank:{} id:{} addr:{} port:{} visible_gpu:{} trainers:{}".format(
self.rank, self.id, self.addr, self.port, self.gpus,
[str(t) for t in self.trainers])
def __eq__(self, pod):
if self.rank != pod.rank or \
self.id != pod.id or \
self.addr != pod.addr or \
self.port != pod.port:
logger.debug("pod {} != pod".format(self, pod))
return False
if len(self.trainers) != len(pod.trainers):
logger.debug("trainers {} != {}".format(self.trainers,
pod.trainers))
return False
for i in range(len(self.trainers)):
if self.trainers[i] != pod.trainers[i]:
logger.debug("trainer {} != {}".format(self.trainers[i],
pod.trainers[i]))
return False
return True
def __ne__(self, pod):
return not self == pod
def parse_response(self, res_pods):
pass
def rank(self):
return self.rank
def get_visible_gpus(self):
r = ""
for g in self.gpus:
r += "{},".format(g)
assert r != "", "this pod {} can't see any gpus".format(self)
r = r[:-1]
return r
def get_logger(log_level, name="root"):
logger = logging.getLogger(name)
logger.setLevel(log_level)
log_handler = logging.StreamHandler()
log_format = logging.Formatter(
'%(levelname)s %(asctime)s %(filename)s:%(lineno)d] %(message)s')
log_handler.setFormatter(log_format)
logger.addHandler(log_handler)
return logger
def get_cluster(node_ips, node_ip, trainer_endpoints, selected_gpus):
assert type(trainer_endpoints) is list, "trainer_endpoints must be list"
cluster = Cluster(hdfs=None)
trainer_rank = 0
for node_rank, ip in enumerate(node_ips):
pod = Pod()
pod.rank = node_rank
pod.addr = ip
cur_node_endpoints = trainer_endpoints[node_rank]
# when use paddlecloud, endpoints may > selected_gpus(user_defined)
assert len(cur_node_endpoints) >= len(
selected_gpus
), "current trainer_endpoints size should be greater equal than selected_gpus size."
for i in range(len(selected_gpus)):
trainer = Trainer()
trainer.gpus.append(selected_gpus[i])
trainer.endpoint = "%s" % (cur_node_endpoints[i])
trainer.rank = trainer_rank
trainer_rank += 1
pod.trainers.append(trainer)
cluster.pods.append(pod)
pod_rank = node_ips.index(node_ip)
return cluster, cluster.pods[pod_rank]
def terminate_local_procs(procs):
for p in procs:
if p.proc.poll() is None:
p.proc.terminate()
if p.log_fn:
p.log_fn.close()
logger.debug("terminate process id:{}".format(p.proc.pid))
#wait all process terminiated
time.sleep(3)
for step in range(0, 50):
alive = False
for p in procs:
if p.proc.poll() is None: # not termniate
os.kill(p.proc.pid, signal.SIGKILL)
alive = True
if not alive:
logger.info("terminate all the procs")
return
time.sleep(3)
logger.fatal("can't kill all process and exit")
exit(1)
def get_host_name_ip():
try:
host_name = socket.gethostname()
host_ip = socket.gethostbyname(host_name)
return host_name, host_ip
except:
return None
def add_arguments(argname, type, default, help, argparser, **kwargs):
"""Add argparse's argument.
Usage:
.. code-block:: python
parser = argparse.ArgumentParser()
add_argument("name", str, "Jonh", "User name.", parser)
args = parser.parse_args()
"""
type = distutils.util.strtobool if type == bool else type
argparser.add_argument(
"--" + argname,
default=default,
type=type,
help=help + ' Default: %(default)s.',
**kwargs)
def find_free_ports(num):
def __free_port():
with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
s.bind(('', 0))
return s.getsockname()[1]
port_set = set()
step = 0
while True:
port = __free_port()
if port not in port_set:
port_set.add(port)
if len(port_set) >= num:
return port_set
step += 1
if step > 100:
print(
"can't find avilable port and use the specified static port now!"
)
return None
return None
def _prepare_trainer_env(cluster, trainer):
proc_env = {
"FLAGS_selected_gpus": "%s" % ",".join([str(g) for g in trainer.gpus]),
"PADDLE_TRAINER_ID": "%d" % trainer.rank,
"PADDLE_CURRENT_ENDPOINT": "%s" % trainer.endpoint,
"PADDLE_TRAINERS_NUM": "%d" % cluster.trainers_nranks(),
"PADDLE_TRAINER_ENDPOINTS": ",".join(cluster.trainers_endpoints())
}
return proc_env
class TrainerProc(object):
def __init__(self):
self.proc = None
self.log_fn = None
self.log_offset = None
self.rank = None
self.local_rank = None
self.cmd = None
def start_local_trainers(cluster,
pod,
training_script,
training_script_args,
log_dir=None):
current_env = copy.copy(os.environ.copy())
#paddle broadcast ncclUniqueId use socket, and
#proxy maybe make trainers unreachable, so delete them.
#if we set them to "", grpc will log error message "bad uri"
#so just delete them.
current_env.pop("http_proxy", None)
current_env.pop("https_proxy", None)
procs = []
for idx, t in enumerate(pod.trainers):
proc_env = _prepare_trainer_env(cluster, t)
current_env.update(proc_env)
logger.debug("trainer proc env:{}".format(current_env))
cmd = [sys.executable, "-u", training_script] + training_script_args
logger.info("start trainer proc:{} env:{}".format(cmd, proc_env))
fn = None
if log_dir is not None:
os.system("mkdir -p {}".format(log_dir))
fn = open("%s/workerlog.%d" % (log_dir, idx), "a")
proc = subprocess.Popen(cmd, env=current_env, stdout=fn, stderr=fn)
else:
proc = subprocess.Popen(cmd, env=current_env)
tp = TrainerProc()
tp.proc = proc
tp.rank = t.rank
tp.local_rank = idx
tp.log_fn = fn
tp.log_offset = fn.tell() if fn else None
tp.cmd = cmd
procs.append(tp)
return procs
def pull_worker_log(tp):
if tp.log_fn:
with open(tp.log_fn.name, 'r') as fin:
fin.seek(tp.log_offset, 0)
for line in fin:
try:
sys.stdout.write(line)
except UnicodeEncodeError:
sys.stdout.write(
'UnicodeEncodeError occurs at this line. '
'Please refer to the original log file "%s"\n' %
tp.log_fn.name)
tp.log_offset = fin.tell()
def watch_local_trainers(procs, nranks):
try:
error = False
error_rank = []
# wait all process finish or one error
alive = False
for p in procs:
if p.log_fn and p.local_rank == 0:
pull_worker_log(p)
ret = p.proc.poll()
if ret is None:
alive = True
elif ret != 0:
error = True
error_rank.append(p.rank)
if error:
terminate_local_procs(procs)
exit(1)
except KeyboardInterrupt:
logger.warning("KeyboardInterrupt, exit")
terminate_local_procs(procs)
raise
except SystemExit:
logger.error(
"ABORT!!! Out of all {} trainers, the trainer process with rank={} was aborted. Please check its log.".
format(nranks, error_rank))
terminate_local_procs(procs)
raise
except:
logger.error(
"ABORT!!! Out of all {} trainers, the trainer process with rank={} was aborted. Please check its log.".
format(nranks, error_rank))
terminate_local_procs(procs)
raise
return alive