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Paddle/python/paddle/distributed/fleet/ascend_utils.py

120 lines
3.8 KiB

# Copyright (c) 2021 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 json
import paddle
from paddle.distributed.fleet.launch_utils import get_cluster, logger, get_host_name_ip, DeviceMode
def _get_ascend_rankfile(rank_table_file_path):
"""
Args:
rank_table_file_path: ascend npu rank file json
{
"status": "completed",
"version": "1.0",
"server_count": "2",
"server_list": [
{
"server_id": "192.168.24.217",
"device": [
{
"device_id": "0",
"device_ip": "192.1.184.23",
"rank_id": "0"
},
{
"device_id": "1",
"device_ip": "192.2.21.93",
"rank_id": "1"
}
]
},
{
"server_id": "192.168.26.177",
"device": [
{
"device_id": "0",
"device_ip": "192.1.94.132",
"rank_id": "2"
},
{
"device_id": "1",
"device_ip": "192.2.94.30",
"rank_id": "3"
}
]
}
]
}
Returns:
node_ips: node ip list
device_count: number of npu per machine
"""
json_data = None
with open(rank_table_file_path) as json_file:
json_data = json.load(json_file)
node_ips = []
device_count = 0
server_list = json_data['server_list']
for server in server_list:
node_ips.append(server['server_id'])
device_list = server['device']
device_count = len(device_list)
return node_ips, device_count
def get_cloud_cluster(rank_table_file=None,
device_mode=DeviceMode.ASCEND_NPU,
start_port=6070):
"""
Args:
rank_table_file: string, ascend npu rank file path
device_mode: DeviceMode(Int)
start_port: the start port of current runtime env
"""
if rank_table_file:
# multi trainers
node_ips, device_count = _get_ascend_rankfile(rank_table_file)
if len(node_ips) == 1:
node_ip = node_ips[0]
else:
node_index = os.environ.get("PADDLE_TRAINER_ID")
node_ip = None
if node_index:
node_ip = node_ips[int(node_index)]
else:
_, node_ip = get_host_name_ip()
assert node_ip in node_ips, "Can't find your local ip {%s} in node_ips: {%s}" \
% (node_ip, node_ips)
else:
# single trainer (single ascend card)
node_ips = ["127.0.0.1"]
node_ip = node_ips[0]
device_count = 1
devices_per_proc = [str(x) for x in range(device_count)]
free_ports = [
x for x in range(start_port, start_port + len(devices_per_proc))
]
trainer_endpoints = []
for ip in node_ips:
trainer_endpoints.append(["%s:%d" % (ip, port) for port in free_ports])
return get_cluster(node_ips, node_ip, trainer_endpoints,
device_mode, devices_per_proc)