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51 lines
1.5 KiB
51 lines
1.5 KiB
3 years ago
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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3 years ago
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import random
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import numpy as np
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import paddle
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from paddle.distributed import fleet
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__all__ = ['init_parallel_env', 'set_random_seed', 'init_fleet_env']
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def init_fleet_env(find_unused_parameters=False):
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strategy = fleet.DistributedStrategy()
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strategy.find_unused_parameters = find_unused_parameters
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fleet.init(is_collective=True, strategy=strategy)
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def init_parallel_env():
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env = os.environ
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dist = 'PADDLE_TRAINER_ID' in env and 'PADDLE_TRAINERS_NUM' in env
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if dist:
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trainer_id = int(env['PADDLE_TRAINER_ID'])
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local_seed = (99 + trainer_id)
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random.seed(local_seed)
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np.random.seed(local_seed)
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paddle.distributed.init_parallel_env()
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def set_random_seed(seed):
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paddle.seed(seed)
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random.seed(seed)
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np.random.seed(seed)
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