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/*
* Copyright (C) 2010-2021 Arm Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* 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
*
* 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.
*/
/* ----------------------------------------------------------------------
* Project: CMSIS NN Library
* Title: arm_pool_q7_HWC.c
* Description: Pooling function implementations
*
* $Date: 20. July 2021
* $Revision: V.1.1.1
*
* Target Processor: Cortex-M cores
*
* -------------------------------------------------------------------- */
#include "arm_nnfunctions.h"
#include "arm_nnsupportfunctions.h"
#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
/**
* @brief A few utility functions used by pooling functions
*
*
*/
static void buffer_scale_back_q15_to_q7(q15_t *buffer, q7_t *target, uint16_t length, uint16_t scale)
{
int i;
for (i = 0; i < length; i++)
{
target[i] = (q7_t)(buffer[i] / scale);
}
}
static void compare_and_replace_if_larger_q7(q7_t *base, // base data
const q7_t *target, // compare target
const uint16_t length // data length
)
{
q7_t *pIn = base;
const q7_t *pCom = target;
union arm_nnword in;
union arm_nnword com;
uint16_t cnt = length >> 2;
while (cnt > 0u)
{
in.word = arm_nn_read_q7x4((const q7_t *)pIn);
com.word = arm_nn_read_q7x4_ia((const q7_t **)&pCom);
// if version
if (com.bytes[0] > in.bytes[0])
in.bytes[0] = com.bytes[0];
if (com.bytes[1] > in.bytes[1])
in.bytes[1] = com.bytes[1];
if (com.bytes[2] > in.bytes[2])
in.bytes[2] = com.bytes[2];
if (com.bytes[3] > in.bytes[3])
in.bytes[3] = com.bytes[3];
arm_nn_write_q7x4_ia(&pIn, in.word);
cnt--;
}
cnt = length & 0x3;
while (cnt > 0u)
{
if (*pCom > *pIn)
{
*pIn = *pCom;
}
pIn++;
pCom++;
cnt--;
}
}
static void accumulate_q7_to_q15(q15_t *base, q7_t *target, const uint16_t length)
{
q15_t *pCnt = base;
q7_t *pV = target;
q31_t v1, v2, vo1, vo2;
uint16_t cnt = length >> 2;
q31_t in;
while (cnt > 0u)
{
q31_t value = arm_nn_read_q7x4_ia((const q7_t **)&pV);
v1 = __SXTB16(__ROR(value, 8));
v2 = __SXTB16(value);
#ifndef ARM_MATH_BIG_ENDIAN
vo2 = __PKHTB(v1, v2, 16);
vo1 = __PKHBT(v2, v1, 16);
#else
vo1 = __PKHTB(v1, v2, 16);
vo2 = __PKHBT(v2, v1, 16);
#endif
in = arm_nn_read_q15x2(pCnt);
arm_nn_write_q15x2_ia(&pCnt, __QADD16(vo1, in));
in = arm_nn_read_q15x2(pCnt);
arm_nn_write_q15x2_ia(&pCnt, __QADD16(vo2, in));
cnt--;
}
cnt = length & 0x3;
while (cnt > 0u)
{
*pCnt++ += *pV++;
cnt--;
}
}
#endif // ARM_MATH_DSP
/**
* @ingroup groupNN
*/
/**
* @addtogroup Pooling
* @{
*/
/**
* @brief Q7 max pooling function
* @param[in, out] 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 Not used
* @param[in,out] Im_out pointer to output tensor
*
* @details
*
* The pooling function is implemented as split x-pooling then
* y-pooling.
*
* This pooling function is input-destructive. Input data is undefined
* after calling this function.
*
*/
void arm_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)
{
(void)bufferA;
#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
/* Run the following code for Cortex-M4 and Cortex-M7 */
int16_t i_x, i_y;
/* first does the pooling along x axis */
for (i_y = 0; i_y < dim_im_in; i_y++)
{
for (i_x = 0; i_x < dim_im_out; i_x++)
{
/* for each output pixel */
q7_t *target = Im_in + (i_y * dim_im_in + i_x) * ch_im_in;
q7_t *win_start;
q7_t *win_stop;
if (i_x * stride - padding < 0)
{
win_start = target;
}
else
{
win_start = Im_in + (i_y * dim_im_in + i_x * stride - padding) * ch_im_in;
}
if (i_x * stride - padding + dim_kernel >= dim_im_in)
{
win_stop = Im_in + (i_y * dim_im_in + dim_im_in) * ch_im_in;
}
else
{
win_stop = Im_in + (i_y * dim_im_in + i_x * stride - padding + dim_kernel) * ch_im_in;
}
/* first step is to copy over initial data */
/* arm_copy_q7(win_start, target, ch_im_in); */
memmove(target, win_start, ch_im_in);
/* start the max operation from the second part */
win_start += ch_im_in;
for (; win_start < win_stop; win_start += ch_im_in)
{
compare_and_replace_if_larger_q7(target, win_start, ch_im_in);
}
}
}
/* then does the pooling along y axis */
for (i_y = 0; i_y < dim_im_out; i_y++)
{
/* for each output row */
q7_t *target = Im_out + i_y * dim_im_out * ch_im_in;
q7_t *row_start;
q7_t *row_end;
/* setting the starting row */
if (i_y * stride - padding < 0)
{
row_start = Im_in;
}
else
{
row_start = Im_in + (i_y * stride - padding) * dim_im_in * ch_im_in;
}
/* setting the stopping row */
if (i_y * stride - padding + dim_kernel >= dim_im_in)
{
row_end = Im_in + dim_im_in * dim_im_in * ch_im_in;
}
else
{
row_end = Im_in + (i_y * stride - padding + dim_kernel) * dim_im_in * ch_im_in;
}
/* copy over the first row */
/* arm_copy_q7(row_start, target, dim_im_out * ch_im_in); */
memmove(target, row_start, dim_im_out * ch_im_in);
/* move over to next row */
row_start += ch_im_in * dim_im_in;
for (; row_start < row_end; row_start += dim_im_in * ch_im_in)
{
compare_and_replace_if_larger_q7(target, row_start, dim_im_out * ch_im_in);
}
}
#else
/* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
int16_t i_ch_in, i_x, i_y;
int16_t k_x, k_y;
for (i_ch_in = 0; i_ch_in < ch_im_in; i_ch_in++)
{
for (i_y = 0; i_y < dim_im_out; i_y++)
{
for (i_x = 0; i_x < dim_im_out; i_x++)
{
int max = -129;
for (k_y = i_y * stride - padding; k_y < i_y * stride - padding + dim_kernel; k_y++)
{
for (k_x = i_x * stride - padding; k_x < i_x * stride - padding + dim_kernel; k_x++)
{
if (k_y >= 0 && k_x >= 0 && k_y < dim_im_in && k_x < dim_im_in)
{
if (Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)] > max)
{
max = Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)];
}
}
}
}
Im_out[i_ch_in + ch_im_in * (i_x + i_y * dim_im_out)] = max;
}
}
}
#endif /* ARM_MATH_DSP */
}
/**
* @brief Q7 average pooling function
* @param[in,out] 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
*
* @details
*
* <b>Buffer size:</b>
*
* bufferA size: 2*dim_im_out*ch_im_in
*
* The pooling function is implemented as split x-pooling then
* y-pooling.
*
* This pooling function is input-destructive. Input data is undefined
* after calling this function.
*
*/
void arm_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)
{
#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
/* Run the following code for Cortex-M4 and Cortex-M7 */
q15_t *buffer = (q15_t *)bufferA;
int16_t i_x, i_y;
int16_t count = 0;
/* first does the pooling along x axis */
for (i_y = 0; i_y < dim_im_in; i_y++)
{
for (i_x = 0; i_x < dim_im_out; i_x++)
{
/* for each output pixel */
q7_t *target = Im_in + (i_y * dim_im_in + i_x) * ch_im_in;
q7_t *win_start;
q7_t *win_stop;
if (i_x * stride - padding < 0)
{
win_start = target;
}
else
{
win_start = Im_in + (i_y * dim_im_in + i_x * stride - padding) * ch_im_in;
}
if (i_x * stride - padding + dim_kernel >= dim_im_in)
{
win_stop = Im_in + (i_y * dim_im_in + dim_im_in) * ch_im_in;
}
else
{
win_stop = Im_in + (i_y * dim_im_in + i_x * stride - padding + dim_kernel) * ch_im_in;
}
/* first step is to copy over initial data */
arm_q7_to_q15_no_shift(win_start, buffer, ch_im_in);
count = 1;
/* start the max operation from the second part */
win_start += ch_im_in;
for (; win_start < win_stop; win_start += ch_im_in)
{
accumulate_q7_to_q15(buffer, win_start, ch_im_in);
count++;
}
buffer_scale_back_q15_to_q7(buffer, target, ch_im_in, count);
}
}
/* then does the pooling along y axis */
for (i_y = 0; i_y < dim_im_out; i_y++)
{
/* for each output row */
q7_t *target = Im_out + i_y * dim_im_out * ch_im_in;
q7_t *row_start;
q7_t *row_end;
/* setting the starting row */
if (i_y * stride - padding < 0)
{
row_start = Im_in;
}
else
{
row_start = Im_in + (i_y * stride - padding) * dim_im_in * ch_im_in;
}
/* setting the stopping row */
if (i_y * stride - padding + dim_kernel >= dim_im_in)
{
row_end = Im_in + dim_im_in * dim_im_in * ch_im_in;
}
else
{
row_end = Im_in + (i_y * stride - padding + dim_kernel) * dim_im_in * ch_im_in;
}
/* copy over the first row */
arm_q7_to_q15_no_shift(row_start, buffer, dim_im_out * ch_im_in);
count = 1;
/* move over to next row */
row_start += ch_im_in * dim_im_in;
for (; row_start < row_end; row_start += dim_im_in * ch_im_in)
{
accumulate_q7_to_q15(buffer, row_start, dim_im_out * ch_im_in);
count++;
}
buffer_scale_back_q15_to_q7(buffer, target, dim_im_out * ch_im_in, count);
}
#else
/* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
(void)bufferA;
int16_t i_ch_in, i_x, i_y;
int16_t k_x, k_y;
for (i_ch_in = 0; i_ch_in < ch_im_in; i_ch_in++)
{
for (i_y = 0; i_y < dim_im_out; i_y++)
{
for (i_x = 0; i_x < dim_im_out; i_x++)
{
int sum = 0;
int count = 0;
for (k_y = i_y * stride - padding; k_y < i_y * stride - padding + dim_kernel; k_y++)
{
for (k_x = i_x * stride - padding; k_x < i_x * stride - padding + dim_kernel; k_x++)
{
if (k_y >= 0 && k_x >= 0 && k_y < dim_im_in && k_x < dim_im_in)
{
sum += Im_in[i_ch_in + ch_im_in * (k_x + k_y * dim_im_in)];
count++;
}
}
}
Im_out[i_ch_in + ch_im_in * (i_x + i_y * dim_im_out)] = sum / count;
}
}
}
#endif /* ARM_MATH_DSP */
}
/**
* @} end of Pooling group
*/