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89 lines
3.1 KiB
89 lines
3.1 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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#include "paddle/operators/net_op.h"
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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(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInputs("X"), "Inputs(X) should not be null");
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auto x_dims = ctx->GetInputsDim("X");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of SumOp should not be null.");
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size_t N = x_dims.size();
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PADDLE_ENFORCE_GT(N, 1, "Input tensors count should > 1.");
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auto in_dim = x_dims[0];
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for (size_t i = 1; i < N; i++) {
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auto dim = x_dims[i];
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PADDLE_ENFORCE(in_dim == dim, "Input tensors must have same shape");
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}
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ctx->SetOutputDim("Out", in_dim);
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ctx->ShareLoD("X", /*->*/ "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 SumGradMaker : public framework::GradOpDescMakerBase {
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public:
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using framework::GradOpDescMakerBase::GradOpDescMakerBase;
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std::vector<std::unique_ptr<framework::OpDescBind>> operator()()
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const override {
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auto x_grads = InputGrad("X");
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std::vector<std::unique_ptr<framework::OpDescBind>> grad_ops;
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grad_ops.reserve(x_grads.size());
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auto og = OutputGrad("Out");
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std::transform(x_grads.begin(), x_grads.end(), std::back_inserter(grad_ops),
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[&og](const std::string& x_grad) {
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auto* grad_op = new framework::OpDescBind();
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grad_op->SetType("scale");
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grad_op->SetInput("X", og);
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grad_op->SetOutput("Out", {x_grad});
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grad_op->SetAttr("scale", 1.0f);
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return std::unique_ptr<framework::OpDescBind>(grad_op);
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});
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return grad_ops;
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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_OPERATOR(sum, ops::SumOp, ops::SumOpMaker, ops::SumGradMaker);
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REGISTER_OP_CPU_KERNEL(sum, ops::SumKernel<paddle::platform::CPUPlace, float>);
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