# Copyright (c) 2022 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 os from argparse import ArgumentParser, REMAINDER env_args_mapping = { 'POD_IP': 'host', 'PADDLE_MASTER': 'master', 'PADDLE_DEVICES': 'devices', 'PADDLE_NNODES': 'nnodes', 'PADDLE_RUN_MODE': 'run_mode', 'PADDLE_LOG_LEVEL': 'log_level', 'PADDLE_NPROC_PER_NODE': 'nproc_per_node', 'PADDLE_JOB_ID': 'job_id', 'PADDLE_RANK': 'rank', 'PADDLE_LOG_DIR': 'log_dir', 'PADDLE_MAX_RESTART': 'max_restart', 'PADDLE_ELASTIC_LEVEL': 'elastic_level', 'PADDLE_ELASTIC_TIMEOUT': 'elastic_timeout', 'PADDLE_SERVER_NUM': 'server_num', 'PADDLE_TRAINER_NUM': 'trainer_num', 'PADDLE_SERVERS_ENDPOINTS': 'servers', 'PADDLE_TRAINERS_ENDPOINTS': 'trainers', 'PADDLE_GLOO_PORT': 'gloo_port', 'PADDLE_WITH_GLOO': 'with_gloo', 'PADDLE_DEVICE_NUM': 'device_num' } def fetch_envs(): os.environ.pop('http_proxy', None) os.environ.pop('https_proxy', None) return os.environ.copy() def parse_args(): parser = ArgumentParser() base_group = parser.add_argument_group("Base Parameters") base_group.add_argument( "--master", type=str, default=None, help="the master/rendezvous server, ip:port") base_group.add_argument( "--legacy", type=bool, default=False, help="use legacy launch") base_group.add_argument( "--rank", type=int, default=-1, help="the node rank") base_group.add_argument( "--log_level", type=str, default="INFO", help="log level. Default INFO") base_group.add_argument( "--nnodes", type=str, default="1", help="the number of nodes, i.e. pod/node number") base_group.add_argument( "--nproc_per_node", type=int, default=None, help="the number of processes in a pod") base_group.add_argument( "--log_dir", type=str, default="log", help="the path for each process's log. Default ./log") base_group.add_argument( "--run_mode", type=str, default=None, help="run mode of the job, collective/ps/ps-heter") base_group.add_argument( "--job_id", type=str, default="default", help="unique id of the job. Default default") base_group.add_argument( "--devices", type=str, default=None, help="accelerate devices. as --gpus,npus,xps") base_group.add_argument( "--device_num", type=int, default=None, help="the number of accelerate devices.") base_group.add_argument("--host", type=str, default=None, help="host ip") base_group.add_argument( "training_script", type=str, help="the full path of py script," "followed by arguments for the " "training script") base_group.add_argument('training_script_args', nargs=REMAINDER) ps_group = parser.add_argument_group("Parameter-Server Parameters") # for parameter server ps_group.add_argument( "--servers", type=str, default='', help="servers endpoints full list") ps_group.add_argument( "--trainers", type=str, default='', help="trainers endpoints full list") ps_group.add_argument( "--trainer_num", type=int, default=None, help="number of trainers") ps_group.add_argument( "--server_num", type=int, default=None, help="number of servers") ps_group.add_argument( "--gloo_port", type=int, default=6767, help="gloo http port") ps_group.add_argument( "--with_gloo", type=str, default="1", help="use gloo or not") # parameter elastic mode elastic_group = parser.add_argument_group("Elastic Parameters") elastic_group.add_argument( "--max_restart", type=int, default=3, help="the times can restart. Default 3") elastic_group.add_argument( "--elastic_level", type=int, default=-1, help="elastic level: -1 disable, 0 failed exit, peers hold, 1 internal restart" ) elastic_group.add_argument( "--elastic_timeout", type=int, default=30, help="seconds to wait before elastic job begin to train") return parser.parse_known_args()