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48 lines
1.6 KiB
48 lines
1.6 KiB
6 years ago
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# Copyright (c) 2018 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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from __future__ import print_function
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from ..layer_helper import LayerHelper, unique_name
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def _allreduce(x, out=None, reduce_type="sum"):
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helper = LayerHelper("allreduce", **locals())
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# Convert string reduce type to op int type
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red_typ_int = 0
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if reduce_type == "sum":
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red_typ_int = 0
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elif reduce_type == "prod":
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red_typ_int = 1
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elif reduce_type == "max":
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red_typ_int = 2
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elif reduce_type == "min":
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red_typ_int = 3
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else:
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raise TypeError("reduce type can only be [sum|prod|max|min]")
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if out is None:
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out = helper.create_variable(
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name=unique_name.generate(".".join([x.name, 'tmp'])),
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shape=x.shape,
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dtype=x.dtype,
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type=x.type,
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persistable=x.persistable,
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stop_gradient=True)
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helper.append_op(
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type='allreduce',
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inputs={'X': [x]},
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outputs={'Out': [out]},
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attrs={"reduce_type": red_typ_int})
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return out
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