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62 lines
2.1 KiB
62 lines
2.1 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/mean_op.h"
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namespace paddle {
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namespace operators {
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class MeanOp : 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_NOT_NULL(ctx.InputVar("X"),
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"Input of MeanOp must be initialized.");
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ctx.Output<Tensor>("Out")->Resize({1});
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}
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};
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class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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MeanOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The input of mean op");
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AddOutput("Out", "The output of mean op").NotInGradient();
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AddComment("Mean Operator");
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}
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};
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class MeanGradOp : 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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ctx.Output<Tensor>(framework::GradVarName("X"))
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->Resize(ctx.Input<Tensor>("X")->dims());
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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(mean, ops::MeanOp, ops::MeanOpMaker, mean_grad, ops::MeanGradOp);
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REGISTER_OP_CPU_KERNEL(mean,
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ops::MeanKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(mean_grad,
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ops::MeanGradKernel<paddle::platform::CPUPlace, float>);
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