/* Copyright (c) 2016 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. */
#ifndef HL_CNN_H_
#define HL_CNN_H_
#include "hl_base.h"
/**
* @brief Maximum pool forward with Mask output.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] channels number of channel.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeX width of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
* @param[out] maskData the location indices of select max data.
*/
extern void hl_maxpool_forward(const int frameCnt,
const real* inputData,
const int channels,
const int height,
const int width,
const int pooledH,
const int pooledW,
const int sizeX,
const int sizeY,
const int strideH,
const int strideW,
const int paddingH,
const int paddingW,
real* tgtData,
const int tgtStride,
real* maskData = NULL);
/**
* @brief Maximum pool backward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[out] outData output data.
* @param[out] outGrad output grad data.
* @param[in] channels number of channel.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeX width of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] scaleA scale.
* @param[in] scaleB scale.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] targetGrad output grad.
* @param[in] outStride stride between output data samples.
*
*/
extern void hl_maxpool_backward(const int frameCnt,
const real* inputData,
const real* outData,
const real* outGrad,
const int channels,
const int height,
const int width,
const int pooledH,
const int pooledW,
const int sizeX,
const int sizeY,
const int strideH,
const int strideW,
const int paddingH,
const int paddingW,
real scaleA,
real scaleB,
real* targetGrad,
const int outStride);
/**
* @brief Averge pool forward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] channels number of channel.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeX width of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
* @param[in] excludeMode whether to consider paddings for size.
*
*/
extern void hl_avgpool_forward(const int frameCnt,
const real* inputData,
const int channels,
const int height,
const int width,
const int pooledH,
const int pooledW,
const int sizeX,
const int sizeY,
const int strideH,
const int strideW,
const int paddingH,
const int paddingW,
real* tgtData,
const int tgtStride,
bool excludeMode);
/**
* @brief Maximum pool backward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] outGrad output grad data.
* @param[in] channels number of channel.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeX width of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[in] scaleA scale.
* @param[in] scaleB scale.
* @param[out] backGrad output grad.
* @param[in] outStride stride between output data samples.
* @param[in] excludeMode whether to consider paddings for size.
*
*/
extern void hl_avgpool_backward(const int frameCnt,
const real* outGrad,
const int channels,
const int height,
const int width,
const int pooledH,
const int pooledW,
const int sizeX,
const int sizeY,
const int strideH,
const int strideW,
int paddingH,
int paddingW,
real scaleA,
real scaleB,
real* backGrad,
const int outStride,
bool excludeMode);
extern void hl_maxpool3D_forward(const int frameCnt,
const real* inputData,
const int channels,
const int depth,
const int height,
const int width,
const int pooledD,
const int pooledH,
const int pooledW,
const int sizeZ,
const int sizeY,
const int sizeX,
const int strideD,
const int strideH,
const int strideW,
const int paddingD,
const int paddingH,
const int paddingW,
real* tgtData,
real* maxPoolIdxData,
const int tgtStride);
extern void hl_maxpool3D_backward(const int frameCnt,
const real* outGrad,
const int channels,
const int depth,
const int height,
const int width,
const int pooledD,
const int pooledH,
const int pooledW,
const int sizeZ,
const int sizeY,
const int sizeX,
const int strideD,
const int strideH,
const int strideW,
const int paddingD,
const int paddingH,
const int paddingW,
real scaleA,
real scaleB,
real* targetGrad,
real* maxPoolIdxData,
const int outStride);
extern void hl_avgpool3D_forward(const int frameCnt,
const real* inputData,
const int channels,
const int depth,
const int height,
const int width,
const int pooledD,
const int pooledH,
const int pooledW,
const int sizeZ,
const int sizeY,
const int sizeX,
const int strideD,
const int strideH,
const int strideW,
const int paddingD,
const int paddingH,
const int paddingW,
real* tgtData,
const int tgtStride);
extern void hl_avgpool3D_backward(const int frameCnt,
const real* outGrad,
const int channels,
const int depth,
const int height,
const int width,
const int pooledD,
const int pooledH,
const int pooledW,
const int sizeZ,
const int sizeY,
const int sizeX,
const int strideD,
const int strideH,
const int strideW,
int paddingD,
int paddingH,
int paddingW,
real scaleA,
real scaleB,
real* backGrad,
const int outStride);
/**
* @brief Bilinear interpolation forward.
*
* @param[in] inData input value.
* @param[in] inImgH input image height.
* @param[in] inImgW input image width.
* @param[in] inputH input batchSize.
* @param[in] inputW input image data dim.
* @param[out] outData output value.
* @param[in] outImgH output image height.
* @param[in] outImgW output image width.
* @param[in] outputH output batchSize.
* @param[in] outputW output image data dim.
* @param[in] numChannels number of channels.
* @param[in] ratioH inImgH / outImgH.
* @param[in] ratioW inImgW / outImgW.
*
*/
extern void hl_bilinear_forward(const real* inData,
const size_t inImgH,
const size_t inImgW,
const size_t inputH,
const size_t inputW,
real* outData,
const size_t outImgH,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels,
const real ratioH,
const real ratioW);
/**
* @brief Bilinear interpolation backward.
*
* @param[out] inGrad input gradient.
* @param[in] inImgH input image height.
* @param[in] inImgW input image width.
* @param[in] inputH input batchSize.
* @param[in] inputW input image data dim.
* @param[in] outGrad output gradient.
* @param[in] outImgH output image height.
* @param[in] outImgW output image width.
* @param[in] outputH output batchSize.
* @param[in] outputW output image data dim.
* @param[in] numChannels number of channels.
* @param[in] ratioH inImgH / outImgH.
* @param[in] ratioW inImgW / outImgW.
*
*/
extern void hl_bilinear_backward(real* inGrad,
const size_t inImgH,
const size_t inImgW,
const size_t inputH,
const size_t inputW,
const real* outGrad,
const size_t outImgH,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels,
const real ratioH,
const real ratioW);
/**
* @brief MaxOut forward.
*
* @param[in] inData input data.
* @param[out] outData output data.
* @param[out] idData output maxId.
* @param[in] batchSize batchSize.
* @param[in] size number of channels * image height * image width.
* @param[in] featLen feature length = image height * image width.
* @param[in] groups number of groups.
*/
extern void hl_maxout_forward(const real* inData,
real* outData,
int* idData,
size_t batchSize,
size_t size,
size_t featLen,
size_t groups);
/**
* @brief MaxOut backward.
*
* @param[out] inGrad input grad data.
* @param[in] outGrad output grad data.
* @param[in] idData output maxId.
* @param[in] batchSize batchSize.
* @param[in] size number of channels * image height * image width.
* @param[in] featLen feature length = image height * image width.
* @param[in] groups number of groups.
*/
extern void hl_maxout_backward(real* inGrad,
const real* outGrad,
const int* idData,
size_t batchSize,
size_t size,
size_t featLen,
size_t groups);
#endif // HL_CNN_H_