/
pixel_unshuffle_op.cc
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/
pixel_unshuffle_op.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/backward.h"
#include "paddle/phi/infermeta/unary.h"
namespace paddle {
namespace operators {
class PixelUnshuffleOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
};
class PixelUnshuffleOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), "
"the input feature data of PixelUnshuffleOp, the layout is "
"[N, C, H, W] or [N, H, W, C].");
AddOutput("Out",
"(Tensor, default Tensor<float>), the output of "
"PixelUnshuffleOp. The layout is [N, C*factor^2, H/factor, "
"W/factor] or [N, H/factor, W/factor, C*factor^2].");
AddAttr<int>("downscale_factor",
"the factor to decrease spatial resolution by.")
.SetDefault(1);
AddAttr<std::string>(
"data_format",
"An optional string from: \"NHWC\", \"NCHW\". "
"Defaults to \"NHWC\", Specify the data format of the input data.")
.SetDefault("NCHW");
AddComment(R"DOC(
Pixel Unshuffle operator
This operator rearranges elements in a tensor of shape :math:`(*, C, H, W)`
to a tensor of shape :math:`(*, C\times r^2, H / r, W / r)`.
This operation is the reversion of PixelShuffle operation.
Please refer to the paper:
`Real-Time Single Image and Video Super-Resolution Using an Efficient
Sub-Pixel Convolutional Neural Network <https://arxiv.org/abs/1609.05158v2>`_
by Shi et. al (2016) for more details.
)DOC");
}
};
template <typename T>
class PixelUnshuffleGradOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
void Apply(GradOpPtr<T> op) const override {
op->SetType("pixel_unshuffle_grad");
op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetAttrMap(this->Attrs());
op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
}
};
class PixelUnshuffleGradOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
DECLARE_INFER_SHAPE_FUNCTOR(pixel_unshuffle, PixelUnshuffleInferShapeFunctor,
PD_INFER_META(phi::PixelUnshuffleInferMeta));
REGISTER_OPERATOR(pixel_unshuffle, ops::PixelUnshuffleOp,
ops::PixelUnshuffleOpMaker,
ops::PixelUnshuffleGradOpMaker<paddle::framework::OpDesc>,
ops::PixelUnshuffleGradOpMaker<paddle::imperative::OpBase>,
PixelUnshuffleInferShapeFunctor);
DECLARE_INFER_SHAPE_FUNCTOR(pixel_unshuffle_grad,
PixelUnshuffleGradInferShapeFunctor,
PD_INFER_META(phi::PixelUnshuffleGradInferMeta));
REGISTER_OPERATOR(pixel_unshuffle_grad, ops::PixelUnshuffleGradOp,
PixelUnshuffleGradInferShapeFunctor);