Paddle/python/paddle/fluid/tests/unittests/ascend_multi_process_collective.py

# Copyright (c) 2019 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 sys
import time

def train(prefix):
    selected_accelerators = os.getenv("FLAGS_selected_accelerators")
    trainer_id = int(os.getenv("PADDLE_TRAINER_ID"))
    worker_endpoints_env = os.getenv("PADDLE_TRAINER_ENDPOINTS")
    current_endpoint = os.getenv("PADDLE_CURRENT_ENDPOINT")
    worker_endpoints = worker_endpoints_env
    trainers_num = len(worker_endpoints.split(','))
    device_ids=os.getenv("PADDLE_WORLD_DEVICE_IDS")
    current_device_id=os.getenv("PADDLE_LOCAL_DEVICE_IDS")

    details = "selected_accelerators:{} worker_endpoints:{} trainers_num:{} current_endpoint:{} trainer_id:{} device_ids:{} device_id:{}"\
            .format(selected_accelerators, worker_endpoints, trainers_num, current_endpoint,trainer_id,device_ids, current_device_id)

    print(details)
    with open("multi_process_{}.check_{}.log".format(prefix, trainer_id), "w") as f:
        f.write(details)


if __name__ == '__main__':
    prefix = sys.argv[1]
    train(prefix)