2020-04-03 06:46:10 -05:00
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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2022-11-29 18:50:04 +08:00
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2022-10-23 20:01:27 +08:00
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from paddle.distributed.utils.launch_utils import (
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get_cluster,
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get_cluster_from_args,
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2022-11-29 18:50:04 +08:00
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get_gpus,
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logger,
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2022-10-23 20:01:27 +08:00
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)
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2021-05-06 15:38:58 +08:00
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__all__ = []
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2020-04-03 06:46:10 -05:00
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2021-03-05 11:18:27 +08:00
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def get_cloud_cluster(args_node_ips, args_node_ip, args_port, selected_devices):
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2020-04-03 06:46:10 -05:00
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"""
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args_node_ips:string, args_node_ip:string, args_port: int, selected_devices:list
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2020-04-03 06:46:10 -05:00
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"""
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# you can automatically get ip info while using paddlecloud multi nodes mode.
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2020-04-03 06:46:10 -05:00
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node_ips = os.getenv("PADDLE_TRAINERS")
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assert node_ips is not None, "PADDLE_TRAINERS should not be None"
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node_ip = os.getenv("POD_IP")
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assert node_ip is not None, "POD_IP should not be None"
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node_rank = os.getenv("PADDLE_TRAINER_ID")
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assert node_rank is not None, "PADDLE_TRAINER_ID should not be None"
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2020-09-16 10:37:26 +08:00
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paddle_ports_num = int(os.getenv("TRAINER_PORTS_NUM"))
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assert paddle_ports_num is not None, "TRAINER_PORTS_NUM should not be None"
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2020-04-03 06:46:10 -05:00
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node_ips = node_ips.split(",")
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num_nodes = len(node_ips)
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node_rank = int(node_rank)
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if node_ip != "127.0.0.1" and node_ip != args_node_ip:
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logger.warning(
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f"Please NOTE: When using paddlecloud, node_ip is \
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automatically got from POD_IP. Your input node_ip: {args_node_ip} doesn't equals to \
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node_ip: {node_ip} from paddlecloud environment."
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)
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2020-04-03 06:46:10 -05:00
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if args_node_ips != "127.0.0.1" and args_node_ips != ",".join(node_ips):
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logger.warning(
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f"Please NOTE: When using paddlecloud, cluster_node_ips is \
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2020-04-03 06:46:10 -05:00
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automatically got from PADDLE_TRAINERS(multi nodes) or POD_IP(single node).\
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Your input cluster_node_ips: {args_node_ips} doesn't equals to IPs: {node_ips} from \
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paddlecloud environment."
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)
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2020-04-03 06:46:10 -05:00
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2020-09-16 10:37:26 +08:00
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# DISTRIBUTED_TRAINER_ENDPOINTS: new environment since paddlecloud 1.8.4
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# e.g: DISTRIBUTED_TRAINER_ENDPOINTS="ip1:port1,ip1:port2,ip1:port3,ip1:port4,ip2:port5,ip2:port6,ip2:port7,ip2:port8"
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trainer_endpoints = os.getenv("DISTRIBUTED_TRAINER_ENDPOINTS")
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if trainer_endpoints is None:
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started_port = args_port
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if num_nodes > 1:
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try:
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paddle_port = int(os.getenv("PADDLE_PORT", ""))
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2022-10-23 20:01:27 +08:00
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if (
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paddle_ports_num >= len(selected_devices)
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and paddle_port != args_port
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):
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logger.warning(f"Use Cloud specified port:{paddle_port}.")
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started_port = paddle_port
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except Exception as e:
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print(e)
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if started_port is None:
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started_port = 6170
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ports = list(range(started_port, started_port + len(selected_devices)))
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trainer_endpoints = []
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for ip in node_ips:
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trainer_endpoints.append([f"{ip}:{port}" for port in ports])
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else:
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trainer_endpoints_ori = trainer_endpoints.split(",")
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trainer_endpoints = []
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assert num_nodes * paddle_ports_num == len(trainer_endpoints_ori)
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for i in range(num_nodes):
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trainer_endpoints.append(
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trainer_endpoints_ori[
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i * paddle_ports_num : (i + 1) * paddle_ports_num
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]
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)
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2020-09-16 10:37:26 +08:00
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2022-10-23 20:01:27 +08:00
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logger.debug(
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f"parsed from args: node_ips:{node_ips} \
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node_ip:{node_ip} node_rank:{node_rank} trainer_endpoints:{trainer_endpoints}"
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)
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2020-09-16 10:37:26 +08:00
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2022-10-23 20:01:27 +08:00
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cluster, pod = get_cluster(
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node_ips, node_ip, trainer_endpoints, selected_devices
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)
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return cluster, cluster.pods[node_rank]
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2020-11-26 10:35:26 +08:00
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def _get_trainers_num():
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return int(os.getenv("PADDLE_TRAINERS_NUM", "1"))
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def get_cluster_and_pod(args):
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# parse arguments, used for cloud-single-machine and local
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selected_devices = get_gpus(args.selected_devices)
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trainers_num = _get_trainers_num()
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logger.debug(
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f"parsed from args trainerss_num:{trainers_num} selected_devices:{selected_devices}"
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)
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cluster = None
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pod = None
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if args.use_paddlecloud and trainers_num != 1:
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cluster, pod = get_cloud_cluster(
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args.cluster_node_ips,
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args.node_ip,
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args.started_port,
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selected_devices,
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)
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logger.info(f"get cluster from cloud:{cluster}")
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else:
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cluster, pod = get_cluster_from_args(args, selected_devices)
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logger.info(f"get cluster from args:{cluster}")
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return cluster, pod
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