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78 lines
2.7 KiB
78 lines
2.7 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/pad_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 PadOp : 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 dim0 = ctx.Input<Tensor>("X")->dims();
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auto paddings = GetAttr<std::vector<std::pair<int, int>>>("paddings");
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std::vector<int> dim1(dim0.size());
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for (int i = 0; i < dim0.size(); ++i) {
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dim1[i] = dim0[i] + paddings[i].first + paddings[i].second;
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}
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ctx.Output<Tensor>("Out")->Resize(paddle::framework::make_ddim(dim1));
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}
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};
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class PadOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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PadOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The input of pad op");
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AddOutput("Out", "The output of pad op");
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AddComment(R"DOC(
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Pad Operator.
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)DOC");
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AddAttr<std::vector<std::pair<int, int>>>(
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"paddings", "The padding rules for each dimension");
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AddAttr<float>("pad_value", "The value to be padded into tensor")
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.SetDefault(0.0f);
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}
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};
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class PadOpGrad : 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"), "Input(X) should not be null");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null");
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auto x_dims = ctx.Input<Tensor>("X")->dims();
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auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
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x_grad->Resize(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(pad, ops::PadOp, ops::PadOpMaker, pad_grad, ops::PadOpGrad);
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REGISTER_OP_CPU_KERNEL(pad, ops::PadKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(pad_grad,
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ops::PadGradKernel<paddle::platform::CPUPlace, float>);
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