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# 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.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import random
import numpy as np
import paddle
from paddle.distributed import fleet
__all__ = ['init_parallel_env', 'set_random_seed', 'init_fleet_env']
def init_fleet_env(find_unused_parameters=False):
strategy = fleet.DistributedStrategy()
strategy.find_unused_parameters = find_unused_parameters
fleet.init(is_collective=True, strategy=strategy)
def init_parallel_env():
env = os.environ
dist = 'PADDLE_TRAINER_ID' in env and 'PADDLE_TRAINERS_NUM' in env
if dist:
trainer_id = int(env['PADDLE_TRAINER_ID'])
local_seed = (99 + trainer_id)
random.seed(local_seed)
np.random.seed(local_seed)
paddle.distributed.init_parallel_env()
def set_random_seed(seed):
paddle.seed(seed)
random.seed(seed)
np.random.seed(seed)