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129 lines
4.7 KiB
129 lines
4.7 KiB
/* Copyright (c) 2016 Baidu, Inc. 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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#ifndef HL_CNN_STUB_H_
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#define HL_CNN_STUB_H_
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#include "hl_cnn.h"
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inline void hl_shrink_col2feature(
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const real * dataCol, size_t channels,
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size_t height, size_t width,
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size_t blockH, size_t blockW,
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size_t strideH, size_t strideW,
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size_t paddingH, size_t paddingW,
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size_t outputH, size_t outputW,
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real* dataIm,
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real alpha, real beta) {}
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inline void hl_expand_feature2col(
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const real* dataIm, size_t channels,
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size_t height, size_t width,
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size_t blockH, size_t blockW,
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size_t strideH, size_t strideW,
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size_t paddingH, size_t paddingW,
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size_t outputH, size_t outputW,
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real* dataCol) {}
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inline void hl_maxpool_forward(
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const int frameCnt, const real* inputData,
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const int channels,
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const int height, const int width,
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const int pooledH, const int pooledW,
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const int sizeX, const int sizeY,
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const int strideH, const int strideW,
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const int paddingH, const int paddingW, real* tgtData) {}
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inline void hl_maxpool_backward(
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const int frameCnt, const real* inputData,
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const real* outData, const real* outGrad,
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const int channels, const int height,
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const int width,
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const int pooledH, const int pooledW,
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const int sizeX, const int sizeY,
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const int strideH, const int strideW,
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const int paddingH, const int paddingW,
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real scaleA, real scaleB,
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real* targetGrad) {}
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inline void hl_avgpool_forward(
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const int frameCnt, const real* inputData,
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const int channels,
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const int height, const int width,
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const int pooledH, const int pooledW,
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const int sizeX, const int sizeY,
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const int strideH, const int strideW,
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const int paddingH, const int paddingW, real* tgtData) {}
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inline void hl_avgpool_backward(
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const int frameCnt, const real* outGrad,
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const int channels, const int height,
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const int width,
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const int pooledH, const int pooledW,
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const int sizeX, const int sizeY,
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const int strideH, const int strideW,
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int paddingH, int paddingW,
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real scaleA, real scaleB,
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real* backGrad) {}
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inline void hl_CMRNorm_forward(
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size_t frameCnt, const real* in, real* scale, real* out,
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size_t channels, size_t height, size_t width, size_t sizeX,
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real alpha, real beta) {}
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inline void hl_CMRNorm_backward(
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size_t frameCnt, const real* inV, const real* scale,
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const real* outV, const real* outDiff, real *inDiff,
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size_t channels, size_t height, size_t width, size_t sizeX,
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real alpha, real beta) {}
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inline void hl_bilinear_forward(const real* inData,
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const size_t inImgH,
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const size_t inImgW,
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const size_t inputH,
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const size_t inputW,
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real* outData,
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const size_t outImgH,
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const size_t outImgW,
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const size_t outputH,
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const size_t outputW,
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const size_t numChannels,
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const real ratioH,
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const real ratioW) {}
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inline void hl_bilinear_backward(real* inGrad,
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const size_t inImgH,
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const size_t inImgW,
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const size_t inputH,
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const size_t inputW,
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const real* outGrad,
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const size_t outImgH,
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const size_t outImgW,
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const size_t outputH,
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const size_t outputW,
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const size_t numChannels,
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const real ratioH,
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const real ratioW) {}
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inline void hl_maxout_forward(
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const real* inData, real* outData, int* idData,
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size_t batchSize, size_t size, size_t featLen, size_t group) {}
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inline void hl_maxout_backward(
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real* inGrad, const real* outGrad, const int* idData,
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size_t batchSize, size_t size, size_t featLen, size_t group) {}
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#endif // HL_CNN_STUB_H_
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