stm32f407-openocd/Drivers/CMSIS/DSP/Source/StatisticsFunctions/arm_logsumexp_f16.c

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2024-06-12 08:32:58 +00:00
/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_logsumexp_f16.c
* Description: LogSumExp
*
* $Date: 23 April 2021
* $Revision: V1.9.0
*
* Target Processor: Cortex-M and Cortex-A cores
* -------------------------------------------------------------------- */
/*
* 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.
*/
#include "dsp/statistics_functions_f16.h"
#if defined(ARM_FLOAT16_SUPPORTED)
#include <limits.h>
#include <math.h>
/**
* @addtogroup LogSumExp
* @{
*/
/**
* @brief Computation of the LogSumExp
*
* In probabilistic computations, the dynamic of the probability values can be very
* wide because they come from gaussian functions.
* To avoid underflow and overflow issues, the values are represented by their log.
* In this representation, multiplying the original exp values is easy : their logs are added.
* But adding the original exp values is requiring some special handling and it is the
* goal of the LogSumExp function.
*
* If the values are x1...xn, the function is computing:
*
* ln(exp(x1) + ... + exp(xn)) and the computation is done in such a way that
* rounding issues are minimised.
*
* The max xm of the values is extracted and the function is computing:
* xm + ln(exp(x1 - xm) + ... + exp(xn - xm))
*
* @param[in] *in Pointer to an array of input values.
* @param[in] blockSize Number of samples in the input array.
* @return LogSumExp
*
*/
#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)
#include "arm_helium_utils.h"
#include "arm_vec_math_f16.h"
float16_t arm_logsumexp_f16(const float16_t *in, uint32_t blockSize)
{
float16_t maxVal;
const float16_t *pIn;
int32_t blkCnt;
_Float16 accum=0.0f16;
_Float16 tmp;
arm_max_no_idx_f16((float16_t *) in, blockSize, &maxVal);
blkCnt = blockSize;
pIn = in;
f16x8_t vSum = vdupq_n_f16(0.0f16);
blkCnt = blockSize >> 3;
while(blkCnt > 0)
{
f16x8_t vecIn = vld1q(pIn);
f16x8_t vecExp;
vecExp = vexpq_f16(vsubq_n_f16(vecIn, maxVal));
vSum = vaddq_f16(vSum, vecExp);
/*
* Decrement the blockSize loop counter
* Advance vector source and destination pointers
*/
pIn += 8;
blkCnt --;
}
/* sum + log */
accum = vecAddAcrossF16Mve(vSum);
blkCnt = blockSize & 0x7;
while(blkCnt > 0)
{
tmp = *pIn++;
accum += expf(tmp - maxVal);
blkCnt--;
}
accum = maxVal + logf(accum);
return (accum);
}
#else
float16_t arm_logsumexp_f16(const float16_t *in, uint32_t blockSize)
{
_Float16 maxVal;
_Float16 tmp;
const float16_t *pIn;
uint32_t blkCnt;
_Float16 accum;
pIn = in;
blkCnt = blockSize;
maxVal = *pIn++;
blkCnt--;
while(blkCnt > 0)
{
tmp = *pIn++;
if (tmp > maxVal)
{
maxVal = tmp;
}
blkCnt--;
}
blkCnt = blockSize;
pIn = in;
accum = 0;
while(blkCnt > 0)
{
tmp = *pIn++;
accum += expf(tmp - maxVal);
blkCnt--;
}
accum = maxVal + logf(accum);
return(accum);
}
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
/**
* @} end of LogSumExp group
*/
#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */