# Copyright (c) 2020 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 import paddle from paddle.fleet.launch_utils import get_cluster, logger def get_cloud_cluster(args_node_ips, selected_gpus, args_port=6170): """ args_node_ips, args_node_ip:string """ #you can automatically get ip info while using paddlecloud multi nodes mode. node_ips = os.getenv("PADDLE_TRAINERS") assert node_ips is not None, "PADDLE_TRAINERS should not be None" node_ip = os.getenv("POD_IP") assert node_ip is not None, "POD_IP should not be None" node_rank = os.getenv("PADDLE_TRAINER_ID") assert node_rank is not None, "PADDLE_TRAINER_ID should not be None" node_ips = node_ips.split(",") num_nodes = len(node_ips) node_rank = int(node_rank) if args_node_ips != "127.0.0.1" and args_node_ips != ",".join(node_ips): logger.warning( "Please NOTE: When using paddlecloud, cluster_node_ips is \ automatically got from PADDLE_TRAINERS(multi nodes) or POD_IP(single node).\ Your input cluster_node_ips: {} doesn't equals to IPs: {} from \ paddlecloud environment.".format(args_node_ips, node_ips)) started_port = args_port print("num_nodes:", num_nodes) if num_nodes > 1: try: paddle_port = int(os.getenv("PADDLE_PORT", "")) paddle_port_num = int(os.getenv("TRAINER_PORTS_NUM", "")) if paddle_port_num >= len( selected_gpus) and paddle_port != args_port: logger.warning("Use Cloud specified port:{}.".format( paddle_port)) started_port = paddle_port except Exception as e: print(e) pass if started_port is None: started_port = 6170 logger.debug("parsed from args:node_ips:{} \ node_ip:{} node_rank:{} started_port:{}" .format(node_ips, node_ip, node_rank, started_port)) ports = [x for x in range(started_port, started_port + len(selected_gpus))] cluster, pod = get_cluster(node_ips, node_ip, ports, selected_gpus) return cluster, cluster.pods[node_rank] def use_paddlecloud(): node_ips = os.getenv("PADDLE_TRAINERS") node_ip = os.getenv("POD_IP") node_rank = os.getenv("PADDLE_TRAINER_ID") if node_ips is None or node_ip is None or node_rank is None: return False else: return True def get_trainers_num(): return int(os.getenv("PADDLE_TRAINERS_NUM", "1"))