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137 lines
4.9 KiB
137 lines
4.9 KiB
// 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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#include "paddle/fluid/operators/reduce_ops/reduce_sum_op.h"
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#include <string>
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namespace paddle {
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namespace framework {
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class OpDesc;
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} // namespace framework
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namespace imperative {
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class OpBase;
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} // namespace imperative
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namespace platform {
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class CPUDeviceContext;
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struct CPUPlace;
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} // namespace platform
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} // namespace paddle
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namespace paddle {
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namespace operators {
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// NOTE: Input(Out) is unnecessary in reduce_sum_grad, and Input(X) needs no
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// buffer
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template <typename T>
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class ReduceSumOpGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetType("reduce_sum_grad");
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op->SetInput("X", this->Input("X"));
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op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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op->SetAttrMap(this->Attrs());
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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}
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const {
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int in_dtype = ctx.Attr<int>("in_dtype");
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if (in_dtype >= 0) {
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return framework::OpKernelType(
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static_cast<framework::proto::VarType::Type>(in_dtype),
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ctx.GetPlace());
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}
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return framework::OpKernelType(
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framework::OperatorWithKernel::IndicateVarDataType(
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ctx, framework::GradVarName("Out")),
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ctx.GetPlace());
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}
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};
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template <typename T>
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class ReduceSumDoubleOpGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetInput("X", this->OutputGrad(framework::GradVarName("X")));
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op->SetOutput("Out", this->InputGrad(framework::GradVarName("Out")));
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op->SetAttrMap(this->Attrs());
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op->SetType("reduce_sum");
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}
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};
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DECLARE_NO_NEED_BUFFER_VARS_INFERER(ReduceSumGradNoNeedBufferVarInferer, "X");
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class ReduceSumVarTypeInference : public paddle::framework::VarTypeInference {
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public:
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void operator()(paddle::framework::InferVarTypeContext* ctx) const override {
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auto data_type = static_cast<paddle::framework::proto::VarType::Type>(
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BOOST_GET_CONST(int, ctx->GetAttr("out_dtype")));
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if (data_type >= 0) {
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ctx->SetOutputDataType("Out", data_type);
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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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class ReduceSumOpMaker : public ops::ReduceOpMaker {
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protected:
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virtual std::string GetName() const { return "reduce_sum"; }
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virtual std::string GetOpType() const { return "Reduce reduce_sum"; }
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};
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REGISTER_OPERATOR(reduce_sum, ops::ReduceOp, ReduceSumOpMaker,
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ops::ReduceSumVarTypeInference,
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ops::ReduceSumOpGradMaker<paddle::framework::OpDesc>,
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ops::ReduceSumOpGradMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(reduce_sum_grad, ops::ReduceGradOp,
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ops::ReduceSumDoubleOpGradMaker<paddle::framework::OpDesc>,
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ops::ReduceSumDoubleOpGradMaker<paddle::imperative::OpBase>,
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ops::ReduceSumGradNoNeedBufferVarInferer);
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REGISTER_OP_CPU_KERNEL(
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reduce_sum, ops::ReduceKernel<paddle::platform::CPUDeviceContext, float,
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ops::SumFunctor>,
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ops::ReduceKernel<paddle::platform::CPUDeviceContext, double,
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ops::SumFunctor>,
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ops::ReduceKernel<paddle::platform::CPUDeviceContext, int, ops::SumFunctor>,
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ops::ReduceKernel<paddle::platform::CPUDeviceContext, int64_t,
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ops::SumFunctor>,
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ops::ReduceKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64, ops::SumFunctor>,
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ops::ReduceKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128,
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ops::SumFunctor>);
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template <typename T>
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using CPUReduceSumGradKernel =
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ops::ReduceSumGradKernel<paddle::platform::CPUDeviceContext, T,
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ops::SumGradFunctor, true>;
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REGISTER_OP_CPU_KERNEL(reduce_sum_grad, CPUReduceSumGradKernel<float>,
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CPUReduceSumGradKernel<double>,
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CPUReduceSumGradKernel<int>,
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CPUReduceSumGradKernel<int64_t>,
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CPUReduceSumGradKernel<paddle::platform::complex64>,
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CPUReduceSumGradKernel<paddle::platform::complex128>);
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