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84 lines
2.9 KiB
84 lines
2.9 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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#include "paddle/operators/sum_op.h"
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#include <vector>
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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class SumOp : 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(const framework::InferShapeContext &ctx) const override {
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PADDLE_ENFORCE(!ctx.MultiInputVar("X").empty(),
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"Input(X) of SumOp should not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
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"Output(Out) of SumOp should not be null.");
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auto ins = ctx.MultiInput<framework::Tensor>("X");
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auto *out = ctx.Output<framework::LoDTensor>("Out");
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int N = ins.size();
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auto in_dim = ins[0]->dims();
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PADDLE_ENFORCE_GT(N, 1, "Input tensors count should > 1.");
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for (int i = 1; i < N; i++) {
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auto dim = ins[i]->dims();
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PADDLE_ENFORCE(in_dim == dim, "Input tensors must have same shape");
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}
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out->Resize(in_dim);
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ctx.ShareLoD(ctx.op().Inputs("X")[0], "Out");
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}
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};
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class SumOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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SumOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "the input tensors of sum operator.").AsDuplicable();
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AddOutput("Out", "the output tensor of sum operator.");
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AddComment(R"DOC(
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Sum the input tensors.
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All the inputs can carry the LoD (Level of Details) information,
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or not. But the output only shares the LoD with the first input.
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)DOC");
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}
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};
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class SumGradOp : 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(const framework::InferShapeContext &ctx) const override {
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auto outputs =
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ctx.MultiOutput<framework::LoDTensor>(framework::GradVarName("X"));
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auto dims = ctx.Input<Tensor>(framework::GradVarName("Out"))->dims();
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for (auto output : outputs) {
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output->Resize(dims);
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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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namespace ops = paddle::operators;
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REGISTER_OP(sum, ops::SumOp, ops::SumOpMaker, sum_grad, ops::SumGradOp);
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REGISTER_OP_CPU_KERNEL(sum, ops::SumKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(sum_grad,
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ops::SumGradKernel<paddle::platform::CPUPlace, float>);
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