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90 lines
2.9 KiB
C++
90 lines
2.9 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#ifndef OPENCV_FAST_CONVOLUTION_HPP
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#define OPENCV_FAST_CONVOLUTION_HPP
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#include "opencv2/core/hal/intrin.hpp"
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#ifndef FAST_CONV_PRAM
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#define FAST_CONV_PRAM
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#if CV_NEON && CV_NEON_AARCH64 // 32 registers.
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#define FAST_CONV_MR 4
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#define FAST_CONV_NR 28
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enum { FAST_VEC_NLANES=4 };
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#elif CV_NEON // 16 registers.
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#define FAST_CONV_MR 4
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#define FAST_CONV_NR 12
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enum { FAST_VEC_NLANES=4 };
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#else // SIMD 128, AVX or AVX2
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#define FAST_CONV_MR 4
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#define FAST_CONV_NR 24
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enum { FAST_VEC_NLANES=4 };
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#endif
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#endif
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namespace cv {
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namespace dnn {
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struct FastConv2d
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{
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int ngroups;
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int K, C, Hk, Wk;
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int stride_y, stride_x;
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int dilation_y, dilation_x;
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int pad_top, pad_bottom, pad_left, pad_right;
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std::vector<float> weightsBuf; // For generic Conv 2D
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std::vector<float> weightsWino63Buf; // For Winograd F(6x6, 3x3).
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std::vector<float> biasBuf;
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bool ifWinograd63 = false;
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bool useAVX2 = checkHardwareSupport(CPU_AVX2);
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bool useNEON = checkHardwareSupport(CPU_NEON);
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};
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// return a FastConv2d instance.
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Ptr<FastConv2d> initFastConv2d(
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int ngroups,
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int K, int C, int Hk, int Wk,
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int stride_x, int stride_y,
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int dilation_x, int dilation_y,
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const std::vector<size_t>& pads_begin,
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const std::vector<size_t>& pads_end,
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float* srcWeights,
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float* srcBias);
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// It contains different computing branches, like winograd, 1x1 conv.
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void runFastConv2d(InputArray _input, OutputArray _output,
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const Ptr<FastConv2d>& conv, int ntasks, const Ptr<ActivationLayer>& actLayer);
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void runDepthwise(InputArray _input, OutputArray _output, const Ptr<FastConv2d>& conv, float minval, float maxval,
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ActivationLayer* activ, bool ifMinMaxAct);
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// winograd init
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void initWinograd63(Ptr<FastConv2d>& conv, float* src_weight, int K, int C);
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int runWinograd63(InputArray _input, OutputArray _output, const Ptr<FastConv2d>& conv, int ntasks,
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float minval, float maxval, ActivationLayer* activ, bool ifMinMaxAct);
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} // namespace dnn
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namespace opt_AVX2
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{
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#if CV_TRY_AVX2
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void convBlock_AVX2(int k, const float *a, const float *b,
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float *c, int ldc, const float *bias,
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float minval, float maxval, bool ifActiv);
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void depthWiseBlock_AVX2(const float *inptr, float *outptr, const float *weights, float biasval, int *ofstab, int *yxtab,
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float minval, float maxval, int Hi, int Wi, int H0, int W0, int ksize, int pad_top, int pad_left,
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int dilation_y, int stride_x, int stride_y, int inner_xleft, int inner_xright, int inner_ytop,
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int inner_ybottom, bool ifMinMaxAct, bool useSIMD, bool is3x3);
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#endif
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} // namespace opt_AVX2
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} // namespace cv
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#endif //OPENCV_FAST_CONVOLUTION_HPP
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