449 lines
13 KiB
C
449 lines
13 KiB
C
/*
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* Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved.
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the License); you may
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* 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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*
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* www.apache.org/licenses/LICENSE-2.0
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*
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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, WITHOUT
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* 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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*/
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/* ----------------------------------------------------------------------
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* Project: CMSIS NN Library
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* Title: arm_pool_q7_HWC.c
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* Description: Pooling function implementations
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*
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* $Date: 17. January 2018
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* $Revision: V.1.0.0
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*
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* Target Processor: Cortex-M cores
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*
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* -------------------------------------------------------------------- */
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#include "arm_math.h"
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#include "arm_nnfunctions.h"
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#if defined (ARM_MATH_DSP)
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/**
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* @brief A few utility functions used by pooling functions
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*
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*
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*/
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static void buffer_scale_back_q15_to_q7(q15_t * buffer, q7_t * target, uint16_t length, uint16_t scale)
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{
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int i;
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for (i = 0; i < length; i++)
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{
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target[i] = (q7_t) (buffer[i] / scale);
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}
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}
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static void compare_and_replace_if_larger_q7(q7_t * base, // base data
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q7_t * target, // compare target
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const uint16_t length // data length
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)
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{
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q7_t *pIn = base;
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q7_t *pCom = target;
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union arm_nnword in;
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union arm_nnword com;
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uint16_t cnt = length >> 2;
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while (cnt > 0u)
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{
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in.word = *__SIMD32(pIn);
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com.word = *__SIMD32(pCom)++;
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// if version
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if (com.bytes[0] > in.bytes[0])
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in.bytes[0] = com.bytes[0];
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if (com.bytes[1] > in.bytes[1])
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in.bytes[1] = com.bytes[1];
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if (com.bytes[2] > in.bytes[2])
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in.bytes[2] = com.bytes[2];
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if (com.bytes[3] > in.bytes[3])
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in.bytes[3] = com.bytes[3];
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*__SIMD32(pIn)++ = in.word;
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cnt--;
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}
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}
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static void accumulate_q7_to_q15(q15_t * base, q7_t * target, const uint16_t length)
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{
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q15_t *pCnt = base;
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q7_t *pV = target;
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q31_t v1, v2, vo1, vo2;
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uint16_t cnt = length >> 2;
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q31_t in;
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while (cnt > 0u)
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{
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q31_t value = *__SIMD32(pV)++;
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v1 = __SXTB16(__ROR(value, 8));
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v2 = __SXTB16(value);
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#ifndef ARM_MATH_BIG_ENDIAN
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vo2 = __PKHTB(v1, v2, 16);
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vo1 = __PKHBT(v2, v1, 16);
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#else
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vo1 = __PKHTB(v1, v2, 16);
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vo2 = __PKHBT(v2, v1, 16);
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#endif
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in = *__SIMD32(pCnt);
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*__SIMD32(pCnt)++ = __QADD16(vo1, in);
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in = *__SIMD32(pCnt);
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*__SIMD32(pCnt)++ = __QADD16(vo2, in);
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cnt--;
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}
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cnt = length & 0x3;
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while (cnt > 0u)
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{
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*pCnt++ += *pV++;
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cnt--;
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}
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}
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#endif // ARM_MATH_DSP
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/**
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* @ingroup groupNN
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*/
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/**
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* @addtogroup Pooling
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* @{
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*/
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/**
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* @brief Q7 max pooling function
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* @param[in, out] 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] 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] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] Im_out pointer to output tensor
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* @return none.
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*
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* @details
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*
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* <b>Buffer size:</b>
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*
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* bufferA size: 0
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*
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* The pooling function is implemented as split x-pooling then
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* y-pooling.
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*
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* This pooling function is input-destructive. Input data is undefined
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* after calling this function.
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*
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*/
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void
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arm_maxpool_q7_HWC(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 uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride, const uint16_t dim_im_out, q7_t * bufferA, q7_t * Im_out)
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{
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#if defined (ARM_MATH_DSP)
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/* Run the following code for Cortex-M4 and Cortex-M7 */
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int16_t i_x, i_y;
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/* first does the pooling along x axis */
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for (i_y = 0; i_y < dim_im_in; i_y++)
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{
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for (i_x = 0; i_x < dim_im_out; i_x++)
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{
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/* for each output pixel */
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q7_t *target = Im_in + (i_y * dim_im_in + i_x) * ch_im_in;
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q7_t *win_start;
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q7_t *win_stop;
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if (i_x * stride - padding < 0)
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{
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win_start = target;
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} else
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{
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win_start = Im_in + (i_y * dim_im_in + i_x * stride - padding) * ch_im_in;
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}
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if (i_x * stride - padding + dim_kernel >= dim_im_in)
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{
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win_stop = Im_in + (i_y * dim_im_in + dim_im_in) * ch_im_in;
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} else
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{
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win_stop = Im_in + (i_y * dim_im_in + i_x * stride - padding + dim_kernel) * ch_im_in;
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}
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/* first step is to copy over initial data */
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/* arm_copy_q7(win_start, target, ch_im_in); */
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memmove(target, win_start, ch_im_in);
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/* start the max operation from the second part */
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win_start += ch_im_in;
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for (; win_start < win_stop; win_start += ch_im_in)
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{
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compare_and_replace_if_larger_q7(target, win_start, ch_im_in);
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}
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}
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}
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/* then does the pooling along y axis */
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for (i_y = 0; i_y < dim_im_out; i_y++)
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{
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/* for each output row */
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q7_t *target = Im_out + i_y * dim_im_out * ch_im_in;
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q7_t *row_start;
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q7_t *row_end;
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/* setting the starting row */
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if (i_y * stride - padding < 0)
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{
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row_start = Im_in;
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} else
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{
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row_start = Im_in + (i_y * stride - padding) * dim_im_in * ch_im_in;
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}
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/* setting the stopping row */
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if (i_y * stride - padding + dim_kernel >= dim_im_in)
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{
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row_end = Im_in + dim_im_in * dim_im_in * ch_im_in;
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} else
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{
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row_end = Im_in + (i_y * stride - padding + dim_kernel) * dim_im_in * ch_im_in;
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}
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/* copy over the first row */
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/* arm_copy_q7(row_start, target, dim_im_out * ch_im_in); */
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memmove(target, row_start, dim_im_out * ch_im_in);
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/* move over to next row */
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row_start += ch_im_in * dim_im_in;
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for (; row_start < row_end; row_start += dim_im_in * ch_im_in)
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{
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compare_and_replace_if_larger_q7(target, row_start, dim_im_out * ch_im_in);
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}
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}
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#else
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/* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
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int16_t i_ch_in, i_x, i_y;
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int16_t k_x, k_y;
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for (i_ch_in = 0; i_ch_in < ch_im_in; i_ch_in++)
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{
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for (i_y = 0; i_y < dim_im_out; i_y++)
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{
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for (i_x = 0; i_x < dim_im_out; i_x++)
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{
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int max = -129;
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for (k_y = i_y * stride - padding; k_y < i_y * stride - padding + dim_kernel; k_y++)
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{
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for (k_x = i_x * stride - padding; k_x < i_x * stride - padding + dim_kernel; k_x++)
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{
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if (k_y >= 0 && k_x >= 0 && k_y < dim_im_in && k_x < dim_im_in)
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{
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if (Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)] > max)
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{
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max = Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)];
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}
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}
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}
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}
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Im_out[i_ch_in + ch_im_in * (i_x + i_y * dim_im_out)] = max;
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}
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}
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}
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#endif /* ARM_MATH_DSP */
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}
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/**
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* @brief Q7 average pooling function
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* @param[in,out] 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] 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] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] Im_out pointer to output tensor
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* @return none.
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*
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* @details
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*
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* <b>Buffer size:</b>
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*
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* bufferA size: 2*dim_im_out*ch_im_in
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*
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* The pooling function is implemented as split x-pooling then
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* y-pooling.
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*
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* This pooling function is input-destructive. Input data is undefined
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* after calling this function.
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*
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*/
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void
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arm_avepool_q7_HWC(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 uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride, const uint16_t dim_im_out, q7_t * bufferA, q7_t * Im_out)
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{
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#if defined (ARM_MATH_DSP)
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/* Run the following code for Cortex-M4 and Cortex-M7 */
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q15_t *buffer = (q15_t *) bufferA;
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int16_t i_x, i_y;
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int16_t count = 0;
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/* first does the pooling along x axis */
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for (i_y = 0; i_y < dim_im_in; i_y++)
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{
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for (i_x = 0; i_x < dim_im_out; i_x++)
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{
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/* for each output pixel */
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q7_t *target = Im_in + (i_y * dim_im_in + i_x) * ch_im_in;
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q7_t *win_start;
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q7_t *win_stop;
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if (i_x * stride - padding < 0)
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{
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win_start = target;
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} else
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{
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win_start = Im_in + (i_y * dim_im_in + i_x * stride - padding) * ch_im_in;
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}
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if (i_x * stride - padding + dim_kernel >= dim_im_in)
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{
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win_stop = Im_in + (i_y * dim_im_in + dim_im_in) * ch_im_in;
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} else
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{
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win_stop = Im_in + (i_y * dim_im_in + i_x * stride - padding + dim_kernel) * ch_im_in;
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}
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/* first step is to copy over initial data */
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arm_q7_to_q15_no_shift(win_start, buffer, ch_im_in);
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count = 1;
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/* start the max operation from the second part */
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win_start += ch_im_in;
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for (; win_start < win_stop; win_start += ch_im_in)
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{
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accumulate_q7_to_q15(buffer, win_start, ch_im_in);
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count++;
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}
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buffer_scale_back_q15_to_q7(buffer, target, ch_im_in, count);
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}
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}
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/* then does the pooling along y axis */
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for (i_y = 0; i_y < dim_im_out; i_y++)
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{
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/* for each output row */
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q7_t *target = Im_out + i_y * dim_im_out * ch_im_in;
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q7_t *row_start;
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q7_t *row_end;
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/* setting the starting row */
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if (i_y * stride - padding < 0)
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{
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row_start = Im_in;
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} else
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{
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row_start = Im_in + (i_y * stride - padding) * dim_im_in * ch_im_in;
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}
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/* setting the stopping row */
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if (i_y * stride - padding + dim_kernel >= dim_im_in)
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{
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row_end = Im_in + dim_im_in * dim_im_in * ch_im_in;
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} else
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{
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row_end = Im_in + (i_y * stride - padding + dim_kernel) * dim_im_in * ch_im_in;
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}
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/* copy over the first row */
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arm_q7_to_q15_no_shift(row_start, buffer, dim_im_out * ch_im_in);
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count = 1;
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/* move over to next row */
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row_start += ch_im_in * dim_im_in;
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for (; row_start < row_end; row_start += dim_im_in * ch_im_in)
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{
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accumulate_q7_to_q15(buffer, row_start, dim_im_out * ch_im_in);
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count++;
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}
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buffer_scale_back_q15_to_q7(buffer, target, dim_im_out * ch_im_in, count);
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}
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#else
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/* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
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int16_t i_ch_in, i_x, i_y;
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int16_t k_x, k_y;
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for (i_ch_in = 0; i_ch_in < ch_im_in; i_ch_in++)
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{
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for (i_y = 0; i_y < dim_im_out; i_y++)
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{
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for (i_x = 0; i_x < dim_im_out; i_x++)
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{
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int sum = 0;
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int count = 0;
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for (k_y = i_y * stride - padding; k_y < i_y * stride - padding + dim_kernel; k_y++)
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{
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for (k_x = i_x * stride - padding; k_x < i_x * stride - padding + dim_kernel; k_x++)
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{
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if (k_y >= 0 && k_x >= 0 && k_y < dim_im_in && k_x < dim_im_in)
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{
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sum += Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)];
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count++;
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}
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}
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}
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Im_out[i_ch_in + ch_im_in * (i_x + i_y * dim_im_out)] = sum / count;
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}
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}
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}
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#endif /* ARM_MATH_DSP */
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}
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/**
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* @} end of Pooling group
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*/
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