# 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.distributed.utils import get_cluster
from paddle.distributed.utils import logger
from paddle.distributed.utils import get_gpus
from paddle.distributed.utils import get_cluster_from_args

__all__ = []


def get_cloud_cluster(args_node_ips, args_node_ip, args_port, selected_devices):
 """
 args_node_ips:string, args_node_ip:string, args_port: int, selected_devices:list
 """
 #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"

 paddle_ports_num = int(os.getenv("TRAINER_PORTS_NUM"))
 assert paddle_ports_num is not None, "TRAINER_PORTS_NUM should not be None"

 node_ips = node_ips.split(",")
 num_nodes = len(node_ips)
 node_rank = int(node_rank)

 if node_ip != "127.0.0.1" and node_ip != args_node_ip:
 logger.warning("Please NOTE: When using paddlecloud, node_ip is \
automatically got from POD_IP. Your input node_ip: {} doesn't equals to \
node_ip: {} from paddlecloud environment.".format(args_node_ip, node_ip))

 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))

 # DISTRIBUTED_TRAINER_ENDPOINTS: new environment since paddlecloud 1.8.4
 # e.g: DISTRIBUTED_TRAINER_ENDPOINTS="ip1:port1,ip1:port2,ip1:port3,ip1:port4,ip2:port5,ip2:port6,ip2:port7,ip2:port8"
 trainer_endpoints = os.getenv("DISTRIBUTED_TRAINER_ENDPOINTS")
 if trainer_endpoints is None:
 started_port = args_port
 if num_nodes > 1:
 try:
 paddle_port = int(os.getenv("PADDLE_PORT", ""))

 if paddle_ports_num >= len(
 selected_devices) 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
 ports = [
 x for x in range(started_port, started_port + len(selected_devices))
 ]
 trainer_endpoints = []
 for ip in node_ips:
 trainer_endpoints.append(["%s:%d" % (ip, port) for port in ports])
 else:
 trainer_endpoints_ori = trainer_endpoints.split(",")
 trainer_endpoints = []
 assert num_nodes * paddle_ports_num == len(trainer_endpoints_ori)
 for i in range(num_nodes):
 trainer_endpoints.append(trainer_endpoints_ori[
 i * paddle_ports_num:(i + 1) * paddle_ports_num])

 logger.debug("parsed from args: node_ips:{} \
 node_ip:{} node_rank:{} trainer_endpoints:{}"
 .format(node_ips, node_ip, node_rank, trainer_endpoints))

 cluster, pod = get_cluster(node_ips, node_ip, trainer_endpoints,
 selected_devices)
 return cluster, cluster.pods[node_rank]


def _get_trainers_num():
 return int(os.getenv("PADDLE_TRAINERS_NUM", "1"))


def get_cluster_and_pod(args):
 # parse arguments, used for cloud-single-machine and local
 selected_devices = get_gpus(args.selected_devices)
 trainers_num = _get_trainers_num()
 logger.debug("parsed from args trainerss_num:{} selected_devices:{}".format(
 trainers_num, selected_devices))

 cluster = None
 pod = None

 if args.use_paddlecloud and trainers_num != 1:
 cluster, pod = get_cloud_cluster(args.cluster_node_ips, args.node_ip,
 args.started_port, selected_devices)
 logger.info("get cluster from cloud:{}".format(cluster))
 else:
 cluster, pod = get_cluster_from_args(args, selected_devices)
 logger.info("get cluster from args:{}".format(cluster))

 return cluster, pod