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160 lines
6.2 KiB
160 lines
6.2 KiB
/* Copyright (c) 2016 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 "TensorType.h"
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namespace paddle {
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/**
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*\brief Depthwise convolution forward. The outputData
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* of depthwise convolution is same with ExpandConvLayer
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* when groups equals inputChannels in ExpandConvLayer.
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*
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* \param[in] inputData input data.
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* \param[in] filterData the Paramters of the depthwise conv layer..
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* \param[in] batchSize batch size of input data.
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* \param[in] outputChannels channels of outputData.
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* \param[in] outputHeight height of outputData.
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* \param[in] outputWidth width of outputData.
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* \param[in] inputChannels channels of inputData.
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* \param[in] inputHeight height of inputData.
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* \param[in] inputWidth width of inputData..
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* \param[in] filterMultiplier equals to outputChannels/groups_.
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* \param[in] filterHeight height of filter.
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* \param[in] filterWidth widht of filter.
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* \param[in] strideH stride size in height direction.
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* \param[in] strideW stride size in width direction.
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* \param[in] paddingH padding size in height direction.
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* \param[in] paddingW padding size in width direction.
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* \param[out] outputData outputData.
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*
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*/
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template <DeviceType Device, class T>
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class DepthwiseConvFunctor {
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public:
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void operator()(const T* inputData,
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const T* filterData,
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int batchSize,
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int outputChannels,
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int outputHeight,
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int outputWidth,
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int inputChannels,
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int inputHeight,
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int inputWidth,
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int filterMultiplier,
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int filterHeight,
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int filterWidth,
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int strideH,
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int strideW,
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int paddingH,
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int paddingW,
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T* outputData);
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};
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/**
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*\brief Functor tot compute the depthwise convolution backprop w.r.t input.
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*
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*
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* \param[in] outputGradData the grad data of output.
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* \param[in] filterData the Paramters of the depthwise conv layer..
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* \param[in] batchSize batch size of input data.
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* \param[in] outputChannels channels of outputData.
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* \param[in] outputHeight height of outputData.
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* \param[in] outputWidth width of outputData.
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* \param[in] inputChannels channels of input data.
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* \param[in] inputHeight height of inputData.
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* \param[in] inputWidth width of inputData.
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* \param[in] filterMultiplier equals to outputChannels/groups_.
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* \param[in] filterHeight height of filter.
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* \param[in] filterWidth widht of filter.
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* \param[in] strideH stride size in height direction.
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* \param[in] strideW stride size in width direction.
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* \param[in] paddingH padding size in height direction.
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* \param[in] paddingW padding size in width direction.
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* \param[out] inputGrad the grad data of input.
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*
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*/
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template <DeviceType Device, class T>
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class DepthwiseConvGradInputFunctor {
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public:
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void operator()(const T* outputGrad,
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const T* filterData,
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int batchSize,
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int outputChannels,
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int outputHeight,
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int outputWidth,
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int inputChannels,
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int inputHeight,
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int inputWidth,
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int filterMultiplier,
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int filterHeight,
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int filterWidth,
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int strideH,
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int strideW,
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int paddingH,
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int paddingW,
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T* inputGrad);
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};
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/**
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*\brief Functor tot compute the depthwise convolution backprop w.r.t filter.
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*
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* \param[in] outputGradData the grad data of output.
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* \param[in] inputData inputData.
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* \param[in] batchSize batch size of input data.
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* \param[in] outputChannels channels of outputData.
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* \param[in] outputHeight height of outputData.
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* \param[in] outputWidth width of outputData.
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* \param[in] inputChannels channels of input data.
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* \param[in] inputHeight height of inputData.
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* \param[in] inputWidth width of inputData.
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* \param[in] filterMultiplier equals to outputChannels/groups_.
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* \param[in] filterHeight height of filter.
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* \param[in] filterWidth widht of filter.
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* \param[in] strideH stride size in height direction.
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* \param[in] strideW stride size in width direction.
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* \param[in] paddingH padding size in height direction.
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* \param[in] paddingW padding size in width direction.
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* \param[in] colData Auxiliary data when calculating filterGrad.
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* \param[in] multiplierData Auxiliary data when calculating filterGrad.
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* \param[out] filterGrad the grad data of filter.
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*
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*/
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template <DeviceType Device, class T>
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class DepthwiseConvGradFilterFunctor {
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public:
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void operator()(const T* outputGrad,
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const T* inputData,
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int batchSize,
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int outputChannels,
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int outputHeight,
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int outputWidth,
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int inputChannels,
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int inputHeight,
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int inputWidth,
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int filterMultiplier,
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int filterHeight,
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int filterWidth,
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int strideH,
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int strideW,
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int paddingH,
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int paddingW,
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T* colData,
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T* filterGrad);
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};
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} // namespace paddle
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