mapingshuo
6 years ago
committed by
GitHub
parent
e81f0228df
commit
e2d849b989
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// Copyright (c) 2019 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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#include "paddle/fluid/operators/seed_op.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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class SeedOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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ctx->SetOutputDim("Out", {1});
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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return framework::OpKernelType(framework::proto::VarType::INT32,
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platform::CPUPlace());
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}
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};
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class SeedOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddOutput("Out", "The output of seed op.");
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AddAttr<int>("seed", "Dropout random seed.").SetDefault(0);
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AddComment(R"DOC(
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Seed Operator.
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(
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seed, ops::SeedOp, ops::SeedOpMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OP_CPU_KERNEL(
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seed, ops::CPUSeedKernel<paddle::platform::CPUDeviceContext, int>);
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// Copyright (c) 2019 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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#pragma once
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename DeviceContext, typename T>
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class CPUSeedKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* out = context.Output<Tensor>("Out");
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auto* out_data = out->mutable_data<T>(context.GetPlace());
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int user_seed = context.Attr<int>("seed");
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// NOTE: fixed seed should only be used in unittest or for debug.
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// Guarantee to use random seed in training.
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std::random_device rnd;
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int seed;
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if (user_seed != 0) {
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seed = user_seed;
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} else {
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seed = rnd();
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}
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out_data[0] = seed;
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}
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};
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,46 @@
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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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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid as fluid
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class TestSeedOpFixSeed(OpTest):
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def setUp(self):
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self.op_type = "seed"
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self.inputs = {}
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self.attrs = {"seed": 123}
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self.outputs = {"Out": np.asarray((123)).astype('int32')}
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def test_check_output(self):
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self.check_output()
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class TestSeedOpDiffSeed(OpTest):
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def setUp(self):
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self.op_type = "seed"
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self.inputs = {}
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self.attrs = {"seed": 0}
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self.outputs = {"Out": np.asarray((123)).astype('int32')}
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def test_check_output(self):
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self.check_output(no_check_set=["Out"])
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if __name__ == '__main__':
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unittest.main()
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