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48 lines
1.6 KiB
48 lines
1.6 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import paddle
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from dataset.voxceleb.voxceleb1 import VoxCeleb1
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def main(args):
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paddle.set_device(args.device)
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# stage1: we must call the paddle.distributed.init_parallel_env() api at the begining
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paddle.distributed.init_parallel_env()
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nranks = paddle.distributed.get_world_size()
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local_rank = paddle.distributed.get_rank()
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# stage2: data prepare
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train_ds = VoxCeleb1('train', target_dir=args.data_dir)
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if __name__ == "__main__":
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# yapf: disable
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parser = argparse.ArgumentParser(__doc__)
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parser.add_argument('--device',
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choices=['cpu', 'gpu'],
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default="cpu",
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help="Select which device to train model, defaults to gpu.")
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parser.add_argument("--data-dir",
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default="./data/",
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type=str,
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help="data directory")
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args = parser.parse_args()
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# yapf: enable
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main(args)
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