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client.py
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client.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 cloudpickle
import datetime
import os
import socket
import sys
import threading
import zmq
from parl.utils import to_str, to_byte, get_ip_address, logger
from parl.remote import remote_constants
import time
class Client(object):
"""Base class for the remote client.
For each training task, there is a global client in the cluster which
submits jobs to the master node. Different `@parl.remote_class` objects
connect to the same global client in a training task.
Attributes:
submit_job_socket (zmq.Context.socket): A socket which submits job to
the master node.
pyfiles (bytes): A serialized dictionary containing the code of python
files in local working directory.
executable_path (str): File path of the executable python script.
start_time (time): A timestamp to record the start time of the program.
"""
def __init__(self, master_address, process_id, distributed_files=[]):
"""
Args:
master_addr (str): ip address of the master node.
process_id (str): id of the process that created the Client.
Should use os.getpid() to get the process id.
distributed_files (list): A list of files to be distributed at all
remote instances(e,g. the configuration
file for initialization) .
"""
self.master_address = master_address
self.process_id = process_id
self.ctx = zmq.Context()
self.lock = threading.Lock()
self.heartbeat_socket_initialized = threading.Event()
self.master_is_alive = True
self.client_is_alive = True
self.executable_path = self.get_executable_path()
self.actor_num = 0
self._create_sockets(master_address)
self.pyfiles = self.read_local_files(distributed_files)
def get_executable_path(self):
"""Return current executable path."""
mod = sys.modules['__main__']
if hasattr(mod, '__file__'):
executable_path = os.path.abspath(mod.__file__)
else:
executable_path = os.getcwd()
executable_path = executable_path[:executable_path.rfind('/')]
return executable_path
def read_local_files(self, distributed_files=[]):
"""Read local python code and store them in a dictionary, which will
then be sent to the job.
Args:
distributed_files (list): A list of files to be distributed at all
remote instances(e,g. the configuration
file for initialization) .
Returns:
A cloudpickled dictionary containing the python code in current
working directory.
"""
pyfiles = dict()
pyfiles['python_files'] = {}
pyfiles['other_files'] = {}
code_files = filter(lambda x: x.endswith('.py'), os.listdir('./'))
try:
for file in code_files:
assert os.path.exists(file)
with open(file, 'rb') as code_file:
code = code_file.read()
pyfiles['python_files'][file] = code
for file in distributed_files:
assert os.path.exists(file)
with open(file, 'rb') as f:
content = f.read()
pyfiles['other_files'][file] = content
except AssertionError as e:
raise Exception(
'Failed to create the client, the file {} does not exist.'.
format(file))
return cloudpickle.dumps(pyfiles)
def _create_sockets(self, master_address):
""" Each client has 1 sockets as start:
(1) submit_job_socket: submits jobs to master node.
"""
# submit_job_socket: submits job to master
self.submit_job_socket = self.ctx.socket(zmq.REQ)
self.submit_job_socket.linger = 0
self.submit_job_socket.setsockopt(
zmq.RCVTIMEO, remote_constants.HEARTBEAT_TIMEOUT_S * 1000)
self.submit_job_socket.connect("tcp://{}".format(master_address))
self.start_time = time.time()
thread = threading.Thread(target=self._reply_heartbeat)
thread.setDaemon(True)
thread.start()
self.heartbeat_socket_initialized.wait()
# check if the master is connected properly
try:
self.submit_job_socket.send_multipart([
remote_constants.CLIENT_CONNECT_TAG,
to_byte(self.heartbeat_master_address),
to_byte(socket.gethostname())
])
_ = self.submit_job_socket.recv_multipart()
except zmq.error.Again as e:
logger.warning("[Client] Can not connect to the master, please "
"check if master is started and ensure the input "
"address {} is correct.".format(master_address))
self.master_is_alive = False
raise Exception("Client can not connect to the master, please "
"check if master is started and ensure the input "
"address {} is correct.".format(master_address))
def _reply_heartbeat(self):
"""Reply heartbeat signals to the specific node."""
socket = self.ctx.socket(zmq.REP)
socket.linger = 0
socket.setsockopt(zmq.RCVTIMEO,
remote_constants.HEARTBEAT_RCVTIMEO_S * 1000)
heartbeat_master_port =\
socket.bind_to_random_port(addr="tcp://*")
self.heartbeat_master_address = "{}:{}".format(get_ip_address(),
heartbeat_master_port)
self.heartbeat_socket_initialized.set()
while self.client_is_alive and self.master_is_alive:
try:
message = socket.recv_multipart()
elapsed_time = datetime.timedelta(
seconds=int(time.time() - self.start_time))
socket.send_multipart([
remote_constants.HEARTBEAT_TAG,
to_byte(self.executable_path),
to_byte(str(self.actor_num)),
to_byte(str(elapsed_time))
])
except zmq.error.Again as e:
logger.warning("[Client] Cannot connect to the master."
"Please check if it is still alive.")
self.master_is_alive = False
socket.close(0)
logger.warning("Client exit replying heartbeat for master.")
def _check_and_monitor_job(self, job_heartbeat_address,
ping_heartbeat_address, max_memory):
""" Sometimes the client may receive a job that is dead, thus
we have to check if this job is still alive before sending it to the actor.
"""
# job_heartbeat_socket: sends heartbeat signal to job
job_heartbeat_socket = self.ctx.socket(zmq.REQ)
job_heartbeat_socket.linger = 0
job_heartbeat_socket.setsockopt(zmq.RCVTIMEO, int(0.9 * 1000))
job_heartbeat_socket.connect("tcp://" + ping_heartbeat_address)
try:
job_heartbeat_socket.send_multipart(
[remote_constants.HEARTBEAT_TAG,
to_byte(str(max_memory))])
job_heartbeat_socket.recv_multipart()
except zmq.error.Again:
job_heartbeat_socket.close(0)
logger.error(
"[Client] connects to a finished job, will try again, ping_heartbeat_address:{}"
.format(ping_heartbeat_address))
return False
job_heartbeat_socket.disconnect("tcp://" + ping_heartbeat_address)
job_heartbeat_socket.connect("tcp://" + job_heartbeat_address)
job_heartbeat_socket.setsockopt(
zmq.RCVTIMEO, remote_constants.HEARTBEAT_TIMEOUT_S * 1000)
# a thread for sending heartbeat signals to job
thread = threading.Thread(
target=self._create_job_monitor, args=(job_heartbeat_socket, ))
thread.setDaemon(True)
thread.start()
return True
def _create_job_monitor(self, job_heartbeat_socket):
"""Send heartbeat signals to check target's status"""
job_is_alive = True
while job_is_alive and self.client_is_alive:
try:
job_heartbeat_socket.send_multipart(
[remote_constants.HEARTBEAT_TAG])
job_message = job_heartbeat_socket.recv_multipart()
stop_job = to_str(job_message[1])
job_address = to_str(job_message[2])
if stop_job == 'True':
logger.error(
'Job {} exceeds max memory usage, will stop this job.'.
format(job_address))
self.lock.acquire()
self.actor_num -= 1
self.lock.release()
job_is_alive = False
else:
time.sleep(remote_constants.HEARTBEAT_INTERVAL_S)
except zmq.error.Again as e:
job_is_alive = False
self.lock.acquire()
self.actor_num -= 1
logger.error(
'[xparl] lost connection with a job, current actor num: {}'
.format(self.actor_num))
self.lock.release()
except zmq.error.ZMQError as e:
break
job_heartbeat_socket.close(0)
def submit_job(self, max_memory):
"""Send a job to the Master node.
When a `@parl.remote_class` object is created, the global client
sends a job to the master node. Then the master node will allocate
a vacant job from its job pool to the remote object.
Args:
max_memory (float): Maximum memory (MB) can be used by each remote
instance, the unit is in MB and default value is
none(unlimited).
Returns:
job_address(str): IP address of the job. None if there is no available CPU in the cluster.
"""
if self.master_is_alive:
while True:
# A lock to prevent multiple actors from submitting job at the same time.
self.lock.acquire()
self.submit_job_socket.send_multipart([
remote_constants.CLIENT_SUBMIT_TAG,
to_byte(self.heartbeat_master_address)
])
message = self.submit_job_socket.recv_multipart()
self.lock.release()
tag = message[0]
if tag == remote_constants.NORMAL_TAG:
job_address = to_str(message[1])
job_heartbeat_address = to_str(message[2])
ping_heartbeat_address = to_str(message[3])
check_result = self._check_and_monitor_job(
job_heartbeat_address, ping_heartbeat_address,
max_memory)
if check_result:
self.lock.acquire()
self.actor_num += 1
self.lock.release()
return job_address
# no vacant CPU resources, cannot submit a new job
elif tag == remote_constants.CPU_TAG:
job_address = None
# wait 1 second to avoid requesting in a high frequency.
time.sleep(1)
return job_address
else:
raise NotImplementedError
else:
raise Exception("Client can not submit job to the master, "
"please check if master is connected.")
return None
GLOBAL_CLIENT = None
def connect(master_address, distributed_files=[]):
"""Create a global client which connects to the master node.
.. code-block:: python
parl.connect(master_address='localhost:1234')
Args:
master_address (str): The address of the Master node to connect to.
distributed_files (list): A list of files to be distributed at all
remote instances(e,g. the configuration
file for initialization) .
Raises:
Exception: An exception is raised if the master node is not started.
"""
assert len(master_address.split(":")) == 2, "please input address in " +\
"{ip}:{port} format"
global GLOBAL_CLIENT
cur_process_id = os.getpid()
if GLOBAL_CLIENT is None:
GLOBAL_CLIENT = Client(master_address, cur_process_id,
distributed_files)
else:
if GLOBAL_CLIENT.process_id != cur_process_id:
GLOBAL_CLIENT = Client(master_address, cur_process_id,
distributed_files)
def get_global_client():
"""Get the global client.
To support process-based programming, we will create a new global client in the new process.
Returns:
The global client.
"""
global GLOBAL_CLIENT
assert GLOBAL_CLIENT is not None, "Cannot get the client to submit the" +\
" job, have you connected to the cluster by calling " +\
"parl.connect(master_ip, master_port)?"
cur_process_id = os.getpid()
if GLOBAL_CLIENT.process_id != cur_process_id:
GLOBAL_CLIENT = Client(GLOBAL_CLIENT.master_address, cur_process_id)
return GLOBAL_CLIENT
def disconnect():
"""Disconnect the global client from the master node."""
global GLOBAL_CLIENT
if GLOBAL_CLIENT is not None:
GLOBAL_CLIENT.client_is_alive = False
GLOBAL_CLIENT = None
else:
logger.info(
"No client to be released. Please make sure that you have call `parl.connect`"
)