add parameter server launch (#18687)

add parameter server launch so that a user can easily launch parameter server

python/paddle/distributed/launch_ps.py

@@ -0,0 +1,151 @@
+# 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.
+
+from __future__ import print_function
+from __future__ import unicode_literals
+import subprocess
+import sys
+import os
+import copy
+from argparse import ArgumentParser, REMAINDER
+
+
+def parse_args():
+    # Optional arguments for the launch helper
+    parser = ArgumentParser(description="Distributed training")
+    parser.add_argument(
+        "--cluster_node_ips",
+        type=str,
+        default="127.0.0.1",
+        help="Paddle cluster nodes ips, such as 192.168.0.16,192.168.0.17..")
+
+    parser.add_argument(
+        "--node_ip",
+        type=str,
+        default="127.0.0.1",
+        help="The current node ip. ")
+
+    parser.add_argument(
+        "--start_port",
+        type=int,
+        default=6170,
+        help="The trainer's start port on a single node")
+
+    parser.add_argument(
+        "--print_config",
+        type=bool,
+        default=True,
+        help="Print the config or not")
+
+    parser.add_argument(
+        "--worker_num", type=int, default=2, help="number of workers")
+
+    parser.add_argument(
+        "--server_num", type=int, default=2, help="number of servers")
+
+    parser.add_argument(
+        "--log_dir",
+        default="logs",
+        type=str,
+        help="The path for each process's log.If it's not setted, the log will printed to default pipe."
+    )
+
+    # positional
+    parser.add_argument(
+        "training_script",
+        type=str,
+        help="The full path to the single GPU training "
+        "program/script to be launched in parallel, "
+        "followed by all the arguments for the "
+        "training script")
+
+    # rest from the training program
+    parser.add_argument('training_script_args', nargs=REMAINDER)
+    return parser.parse_args()
+
+
+def start_procs(args):
+    worker_num = args.worker_num
+    server_num = args.server_num
+    start_port = args.start_port
+    default_env = os.environ.copy()
+    current_env = copy.copy(default_env)
+    current_env.pop("http_proxy", None)
+    current_env.pop("https_proxy", None)
+    procs = []
+    cmds = []
+    log_fns = []
+    ports = range(start_port, start_port + server_num, 1)
+    endpoints = ",".join(["127.0.0.1:" + str(x) for x in ports])
+    for i in range(server_num):
+        current_env.update({
+            "TRAINER_NUM": str(worker_num),
+            "CURRENT_ID": str(i),
+            "ENDPOINTS": endpoints,
+            "TRAINING_ROLE": "PSERVER"
+        })
+        cmd = [sys.executable, "-u", args.training_script
+               ] + args.training_script_args
+        cmds.append(cmd)
+        print(cmd)
+        if args.log_dir is not None:
+            os.system("mkdir -p {}".format(args.log_dir))
+            fn = open("%s/serverlog.%d" % (args.log_dir, i), "w")
+            log_fns.append(fn)
+            proc = subprocess.Popen(cmd, env=current_env, stdout=fn, stderr=fn)
+        else:
+            proc = subprocess.Popen(cmd, env=current_env)
+        procs.append(proc)
+
+    for i in range(worker_num):
+        current_env.update({
+            "ENDPOINTS": endpoints,
+            "TRAINER_NUM": str(worker_num),
+            "TRAINING_ROLE": "TRAINER",
+            "CURRENT_ID": str(i)
+        })
+        cmd = [sys.executable, "-u", args.training_script
+               ] + args.training_script_args
+        print(cmd)
+        cmds.append(cmd)
+        if args.log_dir is not None:
+            os.system("mkdir -p {}".format(args.log_dir))
+            fn = open("%s/workerlog.%d" % (args.log_dir, i), "w")
+            log_fns.append(fn)
+            proc = subprocess.Popen(cmd, env=current_env, stdout=fn, stderr=fn)
+        else:
+            proc = subprocess.Popen(cmd, env=current_env)
+        procs.append(proc)
+
+    for i in range(0, len(procs)):
+        proc = procs[i]
+
+        proc.wait()
+        if len(log_fns) > 0:
+            log_fns[i].close()
+
+        if proc.returncode != 0:
+            raise subprocess.CalledProcessError(
+                returncode=procs[i].returncode, cmd=cmds[i])
+
+
+def launch():
+    args = parse_args()
+    if args.print_config:
+        start_procs(args)
+
+
+# server num, worker num        
+if __name__ == "__main__":
+    launch()