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66 lines
2.2 KiB
66 lines
2.2 KiB
/* 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 SumKernel : 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 ins = context.MultiInput<Tensor>("X");
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auto* out = context.Output<Tensor>("Out");
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out->mutable_data<T>(context.GetPlace());
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auto place = context.GetEigenDevice<Place>();
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auto result = EigenVector<T>::Flatten(*out);
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int N = ins.size();
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auto in = EigenVector<T>::Flatten(*(ins[0]));
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result.device(place) = in;
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for (int i = 1; i < N; i++) {
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auto in = EigenVector<T>::Flatten(*(ins[i]));
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result.device(place) = result + in;
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}
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}
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};
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template <typename Place, typename T>
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class SumGradKernel : 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* input = context.Input<Tensor>(framework::GradVarName("Out"));
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auto outs = context.MultiOutput<Tensor>(framework::GradVarName("X"));
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for (auto out : outs) {
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out->mutable_data<T>(context.GetPlace());
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}
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auto place = context.GetEigenDevice<Place>();
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auto in = EigenVector<T>::Flatten(*input);
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for (auto out : outs) {
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auto result = EigenVector<T>::Flatten(*out);
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result.device(place) = in;
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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