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110 lines
4.0 KiB
110 lines
4.0 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/framework/op_version_registry.h"
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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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if (ctx->Attrs().Get<bool>("flatten")) {
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ctx->SetOutputDim(
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"Out",
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framework::make_ddim({framework::product(ctx->GetInputDim("X"))}));
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} else {
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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}
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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 dimension to accumulate along. -1 means the last "
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"dimension [default -1].")
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.SetDefault(-1);
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AddAttr<bool>("flatten",
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"Whether to compute the cumsum over the flattened array. "
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"[default false].")
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.SetDefault(false);
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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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template <typename T>
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class CumsumGradMaker : 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> grad_op) const override {
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grad_op->SetType("cumsum");
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grad_op->SetInput("X", this->OutputGrad("Out"));
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grad_op->SetOutput("Out", this->InputGrad("X"));
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grad_op->SetAttr("axis", BOOST_GET_CONST(int, this->GetAttr("axis")));
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grad_op->SetAttr("flatten",
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BOOST_GET_CONST(bool, this->GetAttr("flatten")));
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grad_op->SetAttr("reverse",
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!BOOST_GET_CONST(bool, this->GetAttr("reverse")));
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grad_op->SetAttr("exclusive",
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BOOST_GET_CONST(bool, this->GetAttr("exclusive")));
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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,
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ops::CumsumGradMaker<paddle::framework::OpDesc>,
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ops::CumsumGradMaker<paddle::imperative::OpBase>);
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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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ops::CumKernel<CPU, ops::CumsumFunctor<int64_t>>);
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REGISTER_OP_VERSION(cumsum)
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.AddCheckpoint(
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R"ROC(
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Upgrade cumsum add a new attribute [flatten].
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)ROC",
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paddle::framework::compatible::OpVersionDesc().NewAttr(
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"flatten",
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"In order to compute the cumsum over the flattened array when the "
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"argument `axis` in python API is None.",
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false));
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