Yu Yang
7 years ago
parent
ae4b7fd575
commit
762a99cc06
@ -1,68 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/add_op.h"
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namespace paddle {
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namespace operators {
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class AddOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of AddOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) of AddOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of AddOp should not be null.");
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auto x_dims = ctx->GetInputDim("X");
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auto y_dims = ctx->GetInputDim("Y");
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PADDLE_ENFORCE_EQ(x_dims, y_dims,
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"Two input of Add Op's dimension must be same.");
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ctx->SetOutputDim("Out", x_dims);
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}
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};
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class AddOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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AddOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The first input of add op");
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AddInput("Y", "The second input of add op");
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AddOutput("Out", "The output of add op");
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AddComment(R"DOC(
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Two Element Add Operator.
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The equation is: Out = X + Y
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)DOC");
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}
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};
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class AddOpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {}
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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_OP(add, ops::AddOp, ops::AddOpMaker, add_grad, ops::AddOpGrad);
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REGISTER_OP_CPU_KERNEL(add, ops::AddKernel<paddle::platform::CPUPlace, float>);
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@ -1,18 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/add_op.h"
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namespace ops = paddle::operators;
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REGISTER_OP_GPU_KERNEL(add, ops::AddKernel<paddle::platform::GPUPlace, float>);
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@ -1,48 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/framework/eigen.h"
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#include "paddle/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 T, int MajorType = Eigen::RowMajor,
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typename IndexType = Eigen::DenseIndex>
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using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
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template <typename Place, typename T>
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class AddKernel : 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* input0 = context.Input<Tensor>("X");
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auto* input1 = context.Input<Tensor>("Y");
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auto* output = context.Output<Tensor>("Out");
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output->mutable_data<T>(context.GetPlace());
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auto X = EigenVector<T>::Flatten(*input0);
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auto Y = EigenVector<T>::Flatten(*input1);
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auto Z = EigenVector<T>::Flatten(*output);
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auto place = context.GetEigenDevice<Place>();
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Z.device(place) = X + Y;
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}
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};
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} // namespace operators
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} // namespace paddle
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@ -1,20 +0,0 @@
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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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class TestAddOp(OpTest):
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def setUp(self):
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self.op_type = "add"
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self.inputs = {
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'X': np.random.random((102, 105)).astype("float32"),
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'Y': np.random.random((102, 105)).astype("float32")
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}
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self.outputs = {'Out': self.inputs['X'] + self.inputs['Y']}
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def test_check_output(self):
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self.check_output()
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if __name__ == "__main__":
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unittest.main()
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