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82 lines
2.9 KiB
82 lines
2.9 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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/fluid/operators/cum_op.h"
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namespace paddle {
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namespace operators {
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class CumOp : 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", ctx->GetInputDim("X"));
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class CumsumOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "Input of cumsum operator");
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AddOutput("Out", "Output of cumsum operator");
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AddAttr<int>("axis",
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"The dimenstion to accumulate along. -1 means the last "
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"dimenstion [default -1].")
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.SetDefault(-1)
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.EqualGreaterThan(-1);
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AddAttr<bool>("exclusive",
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"Whether to perform exclusive cumsum. [default false].")
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.SetDefault(false);
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AddAttr<bool>("reverse",
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"If true, the cumsum is performed in the reversed direction. "
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"[default false].")
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.SetDefault(false);
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AddComment(R"DOC(
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The cumulative sum of the elements along a given axis.
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By default, the first element of the result is the same of the first element of
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the input. If exlusive is true, the first element of the result is 0.
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)DOC");
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}
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};
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class CumsumGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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protected:
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto *grad_op = new framework::OpDesc();
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grad_op->SetType("cumsum");
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grad_op->SetInput("X", OutputGrad("Out"));
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grad_op->SetOutput("Out", InputGrad("X"));
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grad_op->SetAttr("axis", Attr<int>("axis"));
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grad_op->SetAttr("reverse", !Attr<bool>("reverse"));
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grad_op->SetAttr("exclusive", Attr<bool>("exclusive"));
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return std::unique_ptr<framework::OpDesc>(grad_op);
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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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using CPU = paddle::platform::CPUDeviceContext;
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REGISTER_OPERATOR(cumsum, ops::CumOp, ops::CumsumOpMaker, ops::CumsumGradMaker);
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REGISTER_OP_CPU_KERNEL(cumsum, ops::CumKernel<CPU, ops::CumsumFunctor<float>>,
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ops::CumKernel<CPU, ops::CumsumFunctor<double>>,
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ops::CumKernel<CPU, ops::CumsumFunctor<int>>);
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