# 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

from paddle import fluid


def train(prefix):
    if fluid.core.is_compiled_with_xpu():
        selected_devices = os.getenv("FLAGS_selected_xpus")
    else:
        selected_devices = os.getenv("FLAGS_selected_gpus")
    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(','))

    name = "selected_devices:{} worker_endpoints:{} trainers_num:{} current_endpoint:{} trainer_id:{}".format(
        selected_devices,
        worker_endpoints,
        trainers_num,
        current_endpoint,
        trainer_id,
    )

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


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