728 lines
33 KiB
C
728 lines
33 KiB
C
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/* ----------------------------------------------------------------------
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* Title: csky_dsp2_nnfunctions.h
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* Description: Public header file for CSI NN Library
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*
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* -------------------------------------------------------------------- */
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#ifndef _CSKY_DSP2_NNFUNCTIONS_H
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#define _CSKY_DSP2_NNFUNCTIONS_H
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#ifdef __cplusplus
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extern "C"
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{
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#endif
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#include"csky_math.h"
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/**
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* @brief Struct for specifying activation function types
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*
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*/
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typedef enum
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{
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CSKY_SIGMOID = 0, /**< Sigmoid activation function */
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CSKY_TANH = 1, /**< Tanh activation function */
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} csky_dsp2_nn_activation_type;
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/**
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* @brief Basic Q7 convolution function
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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*/
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void csky_dsp2_convolve_HWC_q7_basic(const q7_t * Im_in,
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const uint16_t dim_im_in,
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const uint16_t ch_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA);
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/**
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* @brief Basic Q15 convolution function
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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*/
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void csky_dsp2_convolve_HWC_q15_basic(const q15_t * Im_in,
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const uint16_t dim_im_in,
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const uint16_t ch_im_in,
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const q15_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const q15_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA);
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/**
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* @brief Fast Q7 convolution function
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This function is the version with full list of optimization tricks, but with
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* some contraints:
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* ch_im_in is multiple of 4
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* ch_im_out is multiple of 2
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*/
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void csky_dsp2_convolve_HWC_q7_fast(const q7_t * Im_in,
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const uint16_t dim_im_in,
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const uint16_t ch_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA);
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/**
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* @brief Fast Q7 convolution function (non-sqaure shape)
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in_x input tensor dimention x
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* @param[in] dim_im_in_y input tensor dimention y
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel_x filter kernel size x
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* @param[in] dim_kernel_y filter kernel size y
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* @param[in] padding_x padding size x
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* @param[in] padding_y padding size y
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* @param[in] stride_x convolution stride x
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* @param[in] stride_y convolution stride y
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This function is the version with full list of optimization tricks, but with
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* some contraints:
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* ch_im_in is multiple of 4
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* ch_im_out is multiple of 2
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*/
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void csky_dsp2_convolve_HWC_q7_fast_nonsquare(const q7_t * Im_in,
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const uint16_t dim_im_in_x,
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const uint16_t dim_im_in_y,
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const uint16_t ch_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel_x,
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const uint16_t dim_kernel_y,
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const uint16_t padding_x,
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const uint16_t padding_y,
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const uint16_t stride_x,
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const uint16_t stride_y,
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out_x,
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const uint16_t dim_im_out_y,
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q15_t * bufferA);
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/**
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* @brief Fast Q7 version of 1x1 convolution (non-sqaure shape)
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in_x input tensor dimention x
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* @param[in] dim_im_in_y input tensor dimention y
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel_x filter kernel size x
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* @param[in] dim_kernel_y filter kernel size y
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* @param[in] padding_x padding size x
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* @param[in] padding_y padding size y
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* @param[in] stride_x convolution stride x
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* @param[in] stride_y convolution stride y
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This function implement convolution with 1x1 kernel size (i.e., dim_kernel_x=1
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* and dim_kernel_y=1). It can be used for
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* second half of MobileNets after depthwise separable convolution.
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*
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* This function is the version with full list of optimization tricks, but with
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* some contraints:
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* ch_im_in is multiple of 4
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* ch_im_out is multiple of 2
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*/
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void csky_dsp2_convolve_1x1_HWC_q7_fast(const q7_t * Im_in,
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const uint16_t dim_im_in_x,
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const uint16_t dim_im_in_y,
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const uint16_t ch_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out_x,
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const uint16_t dim_im_out_y,
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q15_t * bufferA);
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/**
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* @brief Q7 version of convolution for RGB image
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This kernel is written exclusively for convolution with ch_im_in
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* equals 3. This applies on the first layer of CNNs which has input
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* image with RGB format.
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*/
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void csky_dsp2_convolve_HWC_q7_RGB(const q7_t * Im_in,
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const uint16_t dim_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA);
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/**
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* @brief Fast Q15 convolution function
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This function is the version with full list of optimization tricks, but with
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* some contraints:
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* ch_im_in is multiple of 2
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* ch_im_out is multiple of 2
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*/
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void csky_dsp2_convolve_HWC_q15_fast(const q15_t * Im_in,
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const uint16_t dim_im_in,
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const uint16_t ch_im_in,
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const q15_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const q15_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA);
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/**
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* @brief Q7 depthwise separable convolution function
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* @param[in] Im_in pointer to input tensor
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* @param[in] dim_im_in input tensor dimention
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* @param[in] ch_im_in number of input tensor channels
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* @param[in] wt pointer to kernel weights
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* @param[in] ch_im_out number of filters, i.e., output tensor channels
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* @param[in] dim_kernel filter kernel size
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* @param[in] padding padding sizes
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* @param[in] stride convolution stride
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* @param[in] bias pointer to bias
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* @param[in] bias_shift amount of left-shift for bias
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @return none.
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*
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* This function is the version with full list of optimization tricks, but with
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* some contraints:
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* ch_im_in is multiple of 2
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* ch_im_out is multiple of 2
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*/
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void csky_dsp2_depthwise_separable_conv_HWC_q7(const q7_t * Im_in,
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const uint16_t dim_im_in,
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const uint16_t ch_im_in,
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const q7_t * wt,
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const uint16_t ch_im_out,
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const uint16_t dim_kernel,
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const uint16_t padding,
|
||
|
|
const uint16_t stride,
|
||
|
|
const q7_t * bias,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
q7_t * Im_out,
|
||
|
|
const uint16_t dim_im_out,
|
||
|
|
q15_t * bufferA);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 depthwise separable convolution function (non-square shape)
|
||
|
|
* @param[in] Im_in pointer to input tensor
|
||
|
|
* @param[in] dim_im_in_x input tensor dimention x
|
||
|
|
* @param[in] dim_im_in_y input tensor dimention y
|
||
|
|
* @param[in] ch_im_in number of input tensor channels
|
||
|
|
* @param[in] wt pointer to kernel weights
|
||
|
|
* @param[in] ch_im_out number of filters, i.e., output tensor channels
|
||
|
|
* @param[in] dim_kernel_x filter kernel size x
|
||
|
|
* @param[in] dim_kernel_y filter kernel size y
|
||
|
|
* @param[in] padding_x padding sizes x
|
||
|
|
* @param[in] padding_y padding sizes y
|
||
|
|
* @param[in] stride_x convolution stride x
|
||
|
|
* @param[in] stride_y convolution stride y
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in,out] Im_out pointer to output tensor
|
||
|
|
* @param[in] dim_im_out_x output tensor dimension x
|
||
|
|
* @param[in] dim_im_out_y output tensor dimension y
|
||
|
|
* @param[in,out] bufferA pointer to buffer space for input
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
* This function is the version with full list of optimization tricks, but with
|
||
|
|
* some contraints:
|
||
|
|
* ch_im_in is multiple of 2
|
||
|
|
* ch_im_out is multiple of 2
|
||
|
|
*/
|
||
|
|
void csky_dsp2_depthwise_separable_conv_HWC_q7_nonsquare(const q7_t * Im_in,
|
||
|
|
const uint16_t dim_im_in_x,
|
||
|
|
const uint16_t dim_im_in_y,
|
||
|
|
const uint16_t ch_im_in,
|
||
|
|
const q7_t * wt,
|
||
|
|
const uint16_t ch_im_out,
|
||
|
|
const uint16_t dim_kernel_x,
|
||
|
|
const uint16_t dim_kernel_y,
|
||
|
|
const uint16_t padding_x,
|
||
|
|
const uint16_t padding_y,
|
||
|
|
const uint16_t stride_x,
|
||
|
|
const uint16_t stride_y,
|
||
|
|
const q7_t * bias,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
q7_t * Im_out,
|
||
|
|
const uint16_t dim_im_out_x,
|
||
|
|
const uint16_t dim_im_out_y,
|
||
|
|
q15_t * bufferA);
|
||
|
|
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 basic fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_q7(const q7_t * pV,
|
||
|
|
const q7_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q7_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 opt fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @param[in,out] vec_buffer pointer to buffer space for input
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_q7_opt(const q7_t * pV,
|
||
|
|
const q7_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q7_t * pOut,
|
||
|
|
q15_t * vec_buffer);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q15 basic fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_q15(const q15_t * pV,
|
||
|
|
const q15_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q15_t * bias,
|
||
|
|
q15_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q15 opt fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_q15_opt(const q15_t * pV,
|
||
|
|
const q15_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q15_t * bias,
|
||
|
|
q15_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Mixed Q15-Q7 fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_mat_q7_vec_q15(const q15_t * pV,
|
||
|
|
const q7_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q15_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Mixed Q15-Q7 opt fully-connected layer function
|
||
|
|
* @param[in] pV pointer to input vector
|
||
|
|
* @param[in] pM pointer to matrix weights
|
||
|
|
* @param[in] dim_vec length of the vector
|
||
|
|
* @param[in] num_of_rows number of rows in weight matrix
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias pointer to bias
|
||
|
|
* @param[in,out] pOut pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_fully_connected_mat_q7_vec_q15_opt(const q15_t * pV,
|
||
|
|
const q7_t * pM,
|
||
|
|
const uint16_t dim_vec,
|
||
|
|
const uint16_t num_of_rows,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q15_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Matrix-Multiplication Kernels for Convolution
|
||
|
|
*
|
||
|
|
* These functions are used within convolution layer functions for
|
||
|
|
* matrix multiplication.
|
||
|
|
*
|
||
|
|
* The implementation is similar to CSI-DSP csky_dsp2_mat_mult functions
|
||
|
|
* with one Q7 and one Q15 operands. The Q15 operand is the im2col
|
||
|
|
* output which is always with 2 columns.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Matrix-multiplication function for convolution
|
||
|
|
* @param[in] pA pointer to operand A
|
||
|
|
* @param[in] pInBuffer pointer to operand B, always conssists of 2 vectors
|
||
|
|
* @param[in] ch_im_out numRow of A
|
||
|
|
* @param[in] numCol_A numCol of A
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias the bias
|
||
|
|
* @param[in,out] pOut pointer to output
|
||
|
|
* @return The function returns the incremented output pointer
|
||
|
|
*/
|
||
|
|
|
||
|
|
q7_t *csky_dsp2_nn_mat_mult_kernel_q7_q15(const q7_t * pA,
|
||
|
|
const q15_t * pInBuffer,
|
||
|
|
const uint16_t ch_im_out,
|
||
|
|
const uint16_t numCol_A,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q7_t * pOut);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Matrix-multiplication function for convolution with reordered columns
|
||
|
|
* @param[in] pA pointer to operand A
|
||
|
|
* @param[in] pInBuffer pointer to operand B, always conssists of 2 vectors
|
||
|
|
* @param[in] ch_im_out numRow of A
|
||
|
|
* @param[in] numCol_A numCol of A
|
||
|
|
* @param[in] bias_shift amount of left-shift for bias
|
||
|
|
* @param[in] out_shift amount of right-shift for output
|
||
|
|
* @param[in] bias the bias
|
||
|
|
* @param[in,out] pOut pointer to output
|
||
|
|
* @return The function returns the incremented output pointer
|
||
|
|
*/
|
||
|
|
|
||
|
|
q7_t *csky_dsp2_nn_mat_mult_kernel_q7_q15_reordered(const q7_t * pA,
|
||
|
|
const q15_t * pInBuffer,
|
||
|
|
const uint16_t ch_im_out,
|
||
|
|
const uint16_t numCol_A,
|
||
|
|
const uint16_t bias_shift,
|
||
|
|
const uint16_t out_shift,
|
||
|
|
const q7_t * bias,
|
||
|
|
q7_t * pOut);
|
||
|
|
|
||
|
|
#ifdef __cplusplus
|
||
|
|
}
|
||
|
|
#endif
|
||
|
|
|
||
|
|
/*
|
||
|
|
* Other functions
|
||
|
|
* These layers are typically not timing critical
|
||
|
|
* Basic implementation is supported here
|
||
|
|
*/
|
||
|
|
|
||
|
|
#ifdef __cplusplus
|
||
|
|
extern "C"
|
||
|
|
{
|
||
|
|
#endif
|
||
|
|
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 RELU function
|
||
|
|
* @param[in,out] data pointer to input
|
||
|
|
* @param[in] size number of elements
|
||
|
|
* @return none.
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_relu_q7(q7_t * data, uint16_t size);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q15 RELU function
|
||
|
|
* @param[in,out] data pointer to input
|
||
|
|
* @param[in] size number of elements
|
||
|
|
* @return none.
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_relu_q15(q15_t * data, uint16_t size);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 neural network activation function using direct table look-up
|
||
|
|
* @param[in,out] data pointer to input
|
||
|
|
* @param[in] size number of elements
|
||
|
|
* @param[in] int_width bit-width of the integer part, assume to be smaller than 3
|
||
|
|
* @param[in] type type of activation functions
|
||
|
|
* @return none.
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_nn_activations_direct_q7(q7_t * data, uint16_t size,
|
||
|
|
uint16_t int_width,
|
||
|
|
csky_dsp2_nn_activation_type type);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q15 neural network activation function using direct table look-up
|
||
|
|
* @param[in,out] data pointer to input
|
||
|
|
* @param[in] size number of elements
|
||
|
|
* @param[in] int_width bit-width of the integer part, assume to be smaller than 3
|
||
|
|
* @param[in] type type of activation functions
|
||
|
|
* @return none.
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_nn_activations_direct_q15(q15_t * data, uint16_t size,
|
||
|
|
uint16_t int_width,
|
||
|
|
csky_dsp2_nn_activation_type type);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 max pooling function
|
||
|
|
* @param[in] Im_in pointer to input tensor
|
||
|
|
* @param[in] dim_im_in input tensor dimention
|
||
|
|
* @param[in] ch_im_in number of input tensor channels
|
||
|
|
* @param[in] dim_kernel filter kernel size
|
||
|
|
* @param[in] padding padding sizes
|
||
|
|
* @param[in] stride convolution stride
|
||
|
|
* @param[in] dim_im_out output tensor dimension
|
||
|
|
* @param[in,out] bufferA pointer to buffer space for input
|
||
|
|
* @param[in,out] Im_out pointer to output tensor
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_maxpool_q7_HWC(q7_t * Im_in,
|
||
|
|
const uint16_t dim_im_in,
|
||
|
|
const uint16_t ch_im_in,
|
||
|
|
const uint16_t dim_kernel,
|
||
|
|
const uint16_t padding,
|
||
|
|
const uint16_t stride,
|
||
|
|
const uint16_t dim_im_out,
|
||
|
|
q7_t * bufferA,
|
||
|
|
q7_t * Im_out);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 average pooling function
|
||
|
|
* @param[in] Im_in pointer to input tensor
|
||
|
|
* @param[in] dim_im_in input tensor dimention
|
||
|
|
* @param[in] ch_im_in number of input tensor channels
|
||
|
|
* @param[in] dim_kernel filter kernel size
|
||
|
|
* @param[in] padding padding sizes
|
||
|
|
* @param[in] stride convolution stride
|
||
|
|
* @param[in] dim_im_out output tensor dimension
|
||
|
|
* @param[in,out] bufferA pointer to buffer space for input
|
||
|
|
* @param[in,out] Im_out pointer to output tensor
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_avepool_q7_HWC(q7_t * Im_in,
|
||
|
|
const uint16_t dim_im_in,
|
||
|
|
const uint16_t ch_im_in,
|
||
|
|
const uint16_t dim_kernel,
|
||
|
|
const uint16_t padding,
|
||
|
|
const uint16_t stride,
|
||
|
|
const uint16_t dim_im_out,
|
||
|
|
q7_t * bufferA,
|
||
|
|
q7_t * Im_out);
|
||
|
|
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q7 softmax function
|
||
|
|
* @param[in] vec_in pointer to input vector
|
||
|
|
* @param[in] dim_vec input vector dimention
|
||
|
|
* @param[out] p_out pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_softmax_q7(const q7_t *vec_in, const uint16_t dim_vec, q7_t *p_out);
|
||
|
|
|
||
|
|
/**
|
||
|
|
* @brief Q15 softmax function
|
||
|
|
* @param[in] vec_in pointer to input vector
|
||
|
|
* @param[in] dim_vec input vector dimention
|
||
|
|
* @param[out] p_out pointer to output vector
|
||
|
|
* @return none.
|
||
|
|
*
|
||
|
|
*/
|
||
|
|
|
||
|
|
void csky_dsp2_softmax_q15(const q15_t *vec_in, const uint16_t dim_vec,
|
||
|
|
q15_t *p_out);
|
||
|
|
|
||
|
|
#ifdef __cplusplus
|
||
|
|
}
|
||
|
|
#endif
|
||
|
|
|
||
|
|
#endif
|