# Copyright (c) 2022 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 argparse

import paddle

from dataset.voxceleb.voxceleb1 import VoxCeleb1


def main(args):
    paddle.set_device(args.device)

    # stage1: we must call the paddle.distributed.init_parallel_env() api at the begining
    paddle.distributed.init_parallel_env()
    nranks = paddle.distributed.get_world_size()
    local_rank = paddle.distributed.get_rank()

    # stage2: data prepare
    train_ds = VoxCeleb1('train', target_dir=args.data_dir)


if __name__ == "__main__":
    # yapf: disable
    parser = argparse.ArgumentParser(__doc__)
    parser.add_argument('--device',
                        choices=['cpu', 'gpu'],
                        default="cpu",
                        help="Select which device to train model, defaults to gpu.")
    parser.add_argument("--data-dir",
                        default="./data/",
                        type=str,
                        help="data directory")
    args = parser.parse_args()
    # yapf: enable

    main(args)