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83 lines
2.7 KiB
83 lines
2.7 KiB
/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <algorithm>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class PixelShuffleOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* in = ctx.Input<framework::Tensor>("X");
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auto* out = ctx.Output<framework::Tensor>("Out");
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out->mutable_data<T>(ctx.GetPlace());
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int factor = ctx.Attr<int>("upscale_factor");
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auto in_dims = in->dims();
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auto o_dims = out->dims();
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framework::Tensor t;
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t.ShareDataWith(*in);
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t.Resize({in_dims[0], o_dims[1], factor, factor, in_dims[2], in_dims[3]});
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std::vector<int> axis = {0, 1, 4, 2, 5, 3};
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framework::Tensor o;
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o.ShareDataWith(*out);
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o.Resize({in_dims[0], o_dims[1], in_dims[2], factor, in_dims[3], factor});
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math::Transpose<DeviceContext, T, 6> trans;
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auto& dev_ctx = ctx.template device_context<DeviceContext>();
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trans(dev_ctx, t, &o, axis);
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out->Resize(o_dims);
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}
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};
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template <typename DeviceContext, typename T>
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class PixelShuffleGradOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* dout = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
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auto* dx = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
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dx->mutable_data<T>(ctx.GetPlace());
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int factor = ctx.Attr<int>("upscale_factor");
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auto do_dims = dout->dims();
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auto dx_dims = dx->dims();
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framework::Tensor t;
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t.ShareDataWith(*dout);
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t.Resize({do_dims[0], do_dims[1], dx_dims[2], factor, dx_dims[3], factor});
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std::vector<int> axis = {0, 1, 3, 5, 2, 4};
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framework::Tensor o;
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o.ShareDataWith(*dx);
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o.Resize({do_dims[0], do_dims[1], factor, factor, dx_dims[2], dx_dims[3]});
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math::Transpose<DeviceContext, T, 6> trans;
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auto& dev_ctx = ctx.template device_context<DeviceContext>();
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trans(dev_ctx, t, &o, axis);
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dx->Resize(dx_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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